STOIC

.gitattributes

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 release_2026_01_15/**/*.xlsx filter=lfs diff=lfs merge=lfs -text
 release_2026_01_15/**/*.json filter=lfs diff=lfs merge=lfs -text
 release_2026_01_15/**/*.pdf filter=lfs diff=lfs merge=lfs -text
-release_2026_03_24/data/aei_raw_1p_api_2026-02-05_to_2026-02-12.csv filter=lfs diff=lfs merge=lfs -text
-release_2026_03_24/data/aei_raw_claude_ai_2026-02-05_to_2026-02-12.csv filter=lfs diff=lfs merge=lfs -text
-release_2026_06_26/data/aei_1p_api_2026-06-26.csv filter=lfs diff=lfs merge=lfs -text
-release_2026_06_26/data/aei_claude_ai_2026-06-26.csv filter=lfs diff=lfs merge=lfs -text
-robot_exposure/robot_exposure_tasks.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -6,8 +6,8 @@ tags:
 - LLM
 - Economic Impacts
 - Anthropic
-license: mit
 viewer: true
+license: mit
 configs:
 - config_name: release_2026_01_15
   data_files:
@@ -17,7 +17,6 @@ configs:
     path: "release_2025_09_15/data/intermediate/aei_raw_1p_api_2025-11-13_to_2025-11-20.csv"
 ---
 
-
 # The Anthropic Economic Index
 
 ## Overview
@@ -28,10 +27,6 @@ The Anthropic Economic Index provides insights into how AI is being incorporated
 
 This repository contains multiple data releases, each with its own documentation:
 
-- **[Labor market impacts](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/labor_market_impacts)**: Job exposure and task penetration data
-- **[Robot Exposure](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/robot_exposure)**: Job and task exposure to robots
-- **[2026-06-26 Release](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/release_2026_06_26)**: Updated analysis with Artifacts and monthly aggregates
-- **[2026-03-24 Release](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/release_2026_03_24)**: Updated analysis with Opus 4.5/4.6 and learning curves
 - **[2026-01-15 Release](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/release_2026_01_15)**: Updated analysis with economic primitives and Sonnet 4.5
 - **[2025-09-15 Release](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/release_2025_09_15)**: Updated analysis with geographic and first-party API data using Sonnet 4
 - **[2025-03-27 Release](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/release_2025_03_27)**: Updated analysis with Claude 3.7 Sonnet data and cluster-level insights
@@ -41,15 +36,11 @@ This repository contains multiple data releases, each with its own documentation
 ## Resources
 
 - [Index Home Page](https://www.anthropic.com/economic-index)
-- [6th report](https://www.anthropic.com/research/economic-index-june-2026-report)
-- [5th report](https://www.anthropic.com/research/economic-index-march-2026-report)
 - [4th report](https://www.anthropic.com/research/anthropic-economic-index-january-2026-report)
 - [3rd report](https://www.anthropic.com/research/anthropic-economic-index-september-2025-report)
 - [2nd report](https://www.anthropic.com/news/anthropic-economic-index-insights-from-claude-sonnet-3-7)
 - [1st report](https://www.anthropic.com/news/the-anthropic-economic-index)
 
-- [What work can robots do?](https://www.anthropic.com/research/what-work-can-robots-do)
-- [Labor market impacts](https://www.anthropic.com/research/labor-market-impacts)
 
 ## License
 
@@ -57,32 +48,10 @@ Data released under CC-BY, code released under MIT License.
 
 ## Contact
 
-For press inquiries, contact press@anthropic.com. For all other questions, reach out to econ-research@anthropic.com.
+For inquiries, contact econ-research@anthropic.com.
 
 ## Citation
 
-### Sixth release
-```
-@online{anthropic2026aeiv6,
-        author = {Maxim Massenkoff and Eva Lyubich and Szymon Sacher and Zoe Hitzig and Shaoyi Zhang and Ryan Heller and Peter McCrory},
-        title = {Anthropic Economic Index report: Cadences},
-        date = {2026-06-26},
-        year = {2026},
-        url = {https://www.anthropic.com/research/economic-index-june-2026-report},
-}
-
-### Fifth release
-
-```
-@online{anthropic2026aeiv5,
-        author = {Maxim Massenkoff and Eva Lyubich and Peter McCrory and Ruth Appel and Ryan Heller},
-        title = {Anthropic Economic Index report: Learning curves},
-        date = {2026-03-24},
-        year = {2026},
-        url = {https://www.anthropic.com/research/economic-index-march-2026-report},
-}
-```
-
 ### Fourth release
 
 ```

release_2026_01_15/data_documentation.md

@@ -1,316 +1,319 @@
-# Data Documentation
-
-This document describes the data sources and variables used in the fourth Anthropic Economic Index (AEI) report.
-
-## Claude.ai Usage Data
-
-### Overview
-The core dataset contains Claude.ai usage metrics aggregated by geography and analysis dimensions (facets).
-
-**Source files**:
-- `aei_raw_claude_ai_2025-11-13_to_2025-11-20.csv` (pre-enrichment data in data/intermediate/)
-
-**Note on data sources**: The AEI raw file contains raw counts and percentages.
-
-### Data Schema
-Each row represents one metric value for a specific geography and facet combination:
-
-| Column | Type | Description |
-|--------|------|-------------|
-| `geo_id` | string | Geographic identifier (ISO-3166-1 country code for countries, ISO 3166-2 region code for country-state, or "GLOBAL"). Examples: "USA", "AGO-LUA" (Angola-Luanda), "ALB-02" (Albania-Fier) (raw version uses 2- instead of 3-letter country codes) |
-| `geography` | string | Geographic level: "country", "country-state", or "global" |
-| `date_start` | date | Start of data collection period |
-| `date_end` | date | End of data collection period |
-| `platform_and_product` | string | "Claude AI (Free and Pro)" |
-| `facet` | string | Analysis dimension (see Facets below) |
-| `level` | integer | Sub-level within facet (0-2) |
-| `variable` | string | Metric name (see Variables below) |
-| `cluster_name` | string | Specific entity within facet (task, pattern, etc.). For intersections, format is "base::category" |
-| `value` | float | Numeric metric value |
-
-### Facets
-
-**Geographic Facets:**
-- **country**: Country-level aggregations
-- **country-state**: Subnational region aggregations (ISO 3166-2 regions globally)
-
-**Content Facets:**
-- **onet_task**: O*NET occupational tasks
-- **collaboration**: Human-AI collaboration patterns
-- **request**: Request complexity levels (0=highest granularity, 1=middle granularity, 2=lowest granularity)
-- **multitasking**: Whether conversation involves single or multiple tasks
-- **human_only_ability**: Whether a human could complete the task without AI assistance
-- **use_case**: Use case categories (work, coursework, personal)
-- **task_success**: Whether the task was successfully completed
-
-**Numeric Facets** (continuous variables with distribution statistics):
-- **human_only_time**: Estimated time for a human to complete the task without AI
-- **human_with_ai_time**: Estimated time for a human to complete the task with AI assistance
-- **ai_autonomy**: Degree of AI autonomy in task completion
-- **human_education_years**: Estimated years of human education required for the task
-- **ai_education_years**: Estimated equivalent years of AI "education" demonstrated
-
-**Intersection Facets:**
-- **onet_task::collaboration**: Intersection of O*NET tasks and collaboration patterns
-- **onet_task::multitasking**: Intersection of O*NET tasks and multitasking status
-- **onet_task::human_only_ability**: Intersection of O*NET tasks and human-only ability
-- **onet_task::use_case**: Intersection of O*NET tasks and use case categories
-- **onet_task::task_success**: Intersection of O*NET tasks and task success
-- **onet_task::human_only_time**: Mean human-only time per O*NET task
-- **onet_task::human_with_ai_time**: Mean human-with-AI time per O*NET task
-- **onet_task::ai_autonomy**: Mean AI autonomy per O*NET task
-- **onet_task::human_education_years**: Mean human education years per O*NET task
-- **onet_task::ai_education_years**: Mean AI education years per O*NET task
-- **request::collaboration**: Intersection of request categories and collaboration patterns
-- **request::multitasking**: Intersection of request categories and multitasking status
-- **request::human_only_ability**: Intersection of request categories and human-only ability
-- **request::use_case**: Intersection of request categories and use case categories
-- **request::task_success**: Intersection of request categories and task success
-- **request::human_only_time**: Mean human-only time per request category
-- **request::human_with_ai_time**: Mean human-with-AI time per request category
-- **request::ai_autonomy**: Mean AI autonomy per request category
-- **request::human_education_years**: Mean human education years per request category
-- **request::ai_education_years**: Mean AI education years per request category
-
-### Core Variables
-
-Variables follow the pattern `{prefix}_{suffix}` with specific meanings:
-
-**From AEI raw file**: `*_count`, `*_pct`
-
-#### Usage Metrics
-- **usage_count**: Total number of conversations/interactions in a geography
-- **usage_pct**: Percentage of total usage (relative to parent geography - global for countries, parent country for country-state regions)
-
-#### Content Facet Metrics
-**O*NET Task Metrics**:
-- **onet_task_count**: Number of conversations using this specific O*NET task
-- **onet_task_pct**: Percentage of geographic total using this task
-- **onet_task_pct_index**: Specialization index comparing task usage to baseline (global for countries, parent country for country-state regions)
-- **onet_task_collaboration_count**: Number of conversations with both this task and collaboration pattern (intersection)
-- **onet_task_collaboration_pct**: Percentage of the base task's total that has this collaboration pattern (sums to 100% within each task)
-
-**Request Metrics**:
-- **request_count**: Number of conversations in this request category level
-- **request_pct**: Percentage of geographic total in this category
-- **request_collaboration_count**: Number of conversations with both this request category and collaboration pattern (intersection)
-- **request_collaboration_pct**: Percentage of the base request's total that has this collaboration pattern (sums to 100% within each request)
-
-**Collaboration Pattern Metrics**:
-- **collaboration_count**: Number of conversations with this collaboration pattern
-- **collaboration_pct**: Percentage of geographic total with this pattern
-
-**Multitasking Metrics**:
-- **multitasking_count**: Number of conversations with this multitasking status
-- **multitasking_pct**: Percentage of geographic total with this status
-
-**Human-Only Ability Metrics**:
-- **human_only_ability_count**: Number of conversations with this human-only ability status
-- **human_only_ability_pct**: Percentage of geographic total with this status
-
-**Use Case Metrics**:
-- **use_case_count**: Number of conversations in this use case category
-- **use_case_pct**: Percentage of geographic total in this category
-
-**Task Success Metrics**:
-- **task_success_count**: Number of conversations with this task success status
-- **task_success_pct**: Percentage of geographic total with this status
-
-#### Numeric Facet Metrics
-For numeric facets (human_only_time, human_with_ai_time, ai_autonomy, human_education_years, ai_education_years), the following distribution statistics are available:
-
-- **{facet}_mean**: Mean value across all conversations
-- **{facet}_median**: Median value across all conversations
-- **{facet}_stdev**: Standard deviation of values
-- **{facet}_mean_ci_lower**: Lower bound of 95% confidence interval for the mean
-- **{facet}_mean_ci_upper**: Upper bound of 95% confidence interval for the mean
-- **{facet}_median_ci_lower**: Lower bound of 95% confidence interval for the median
-- **{facet}_median_ci_upper**: Upper bound of 95% confidence interval for the median
-- **{facet}_count**: Total number of observations for this facet
-- **{facet}_histogram_count**: Count of observations in each histogram bin (one row per bin, bin range in cluster_name, e.g., "[1.0, 1.0)")
-- **{facet}_histogram_pct**: Percentage of observations in each histogram bin (one row per bin)
-
-For numeric intersection facets (e.g., onet_task::human_only_time), the same metrics are available per category (e.g., per O*NET task), with cluster_name containing the category identifier:
-- **{base}_{numeric}_mean**: Mean value for this category
-- **{base}_{numeric}_median**: Median value for this category
-- **{base}_{numeric}_stdev**: Standard deviation for this category
-- **{base}_{numeric}_count**: Number of observations for this category
-- **{base}_{numeric}_mean_ci_lower/upper**: 95% CI bounds for the mean
-- **{base}_{numeric}_median_ci_lower/upper**: 95% CI bounds for the median
-
-#### Special Values
-- **not_classified**: Indicates data that was filtered for privacy protection or could not be classified
-- **none**: Indicates the absence of the attribute (e.g., no collaboration, no task selected)
-
-### Data Processing Notes
-- **Minimum Observations**: 200 conversations per country, 100 per country-state region (applied in enrichment step, not raw preprocessing)
-- **not_classified**:
-  - For regular facets: Captures filtered/unclassified conversations
-  - For intersection facets: Each base cluster has its own not_classified (e.g., "task1::not_classified")
-- **Intersection Percentages**: Calculated relative to base cluster totals, ensuring each base cluster's percentages sum to 100%
-- **Country Codes**: ISO-3166-1 format for countries, three letter codes in the enriched file (e.g., "USA", "GBR", "FRA") and two letter codes in the raw file (e.g., "US", "GB", "FR"); ISO 3166-2 format for country-state regions (e.g., "AGO-LUA", "ALB-02" in enriched file, or "US-CA" in raw file)
-- **Variable Definitions**: See Core Variables section above
-
-## 1P API Usage Data
-
-### Overview
-Dataset containing first-party API usage metrics along various dimensions based on a sample of 1P API traffic and analyzed using privacy-preserving methods.
-
-**Note**: Unlike Claude.ai data, API data has **no geographic breakdowns** (no country or country-state facets). All API metrics are reported at global level only (`geography: "global"`, `geo_id: "GLOBAL"`).
-
-**Source file**: `aei_raw_1p_api_2025-11-13_to_2025-11-20.csv` (in data/intermediate/)
-
-### Data Schema
-Each row represents one metric value for a specific facet combination at global level:
-
-| Column | Type | Description |
-|--------|------|-------------|
-| `geo_id` | string | Geographic identifier (always "GLOBAL" for API data) |
-| `geography` | string | Geographic level (always "global" for API data) |
-| `date_start` | date | Start of data collection period |
-| `date_end` | date | End of data collection period |
-| `platform_and_product` | string | "1P API" |
-| `facet` | string | Analysis dimension (see Facets below) |
-| `level` | integer | Sub-level within facet (0-2) |
-| `variable` | string | Metric name (see Variables below) |
-| `cluster_name` | string | Specific entity within facet. For intersections, format is "base::category" or "base::index"/"base::count" for mean value metrics |
-| `value` | float | Numeric metric value |
-
-### Facets
-
-**Content Facets:**
-- **onet_task**: O*NET occupational tasks
-- **collaboration**: Human-AI collaboration patterns
-- **request**: Request categories (hierarchical levels 0-2 from bottom-up taxonomy)
-- **multitasking**: Whether conversation involves single or multiple tasks
-- **human_only_ability**: Whether a human could complete the task without AI assistance
-- **use_case**: Use case categories (work, coursework, personal)
-- **task_success**: Whether the task was successfully completed
-
-**Numeric Facets** (continuous variables with distribution statistics):
-- **human_only_time**: Estimated time for a human to complete the task without AI
-- **human_with_ai_time**: Estimated time for a human to complete the task with AI assistance
-- **ai_autonomy**: Degree of AI autonomy in task completion
-- **human_education_years**: Estimated years of human education required for the task
-- **ai_education_years**: Estimated equivalent years of AI "education" demonstrated
-
-**Intersection Facets:**
-- **onet_task::collaboration**: Intersection of O*NET tasks and collaboration patterns
-- **onet_task::multitasking**: Intersection of O*NET tasks and multitasking status
-- **onet_task::human_only_ability**: Intersection of O*NET tasks and human-only ability
-- **onet_task::use_case**: Intersection of O*NET tasks and use case categories
-- **onet_task::task_success**: Intersection of O*NET tasks and task success
-- **onet_task::human_only_time**: Mean human-only time per O*NET task
-- **onet_task::human_with_ai_time**: Mean human-with-AI time per O*NET task
-- **onet_task::ai_autonomy**: Mean AI autonomy per O*NET task
-- **onet_task::human_education_years**: Mean human education years per O*NET task
-- **onet_task::ai_education_years**: Mean AI education years per O*NET task
-- **onet_task::cost**: Mean cost per O*NET task (indexed, 1.0 = average)
-- **onet_task::prompt_tokens**: Mean prompt tokens per O*NET task (indexed, 1.0 = average)
-- **onet_task::completion_tokens**: Mean completion tokens per O*NET task (indexed, 1.0 = average)
-- **request::collaboration**: Intersection of request categories and collaboration patterns
-- **request::multitasking**: Intersection of request categories and multitasking status
-- **request::human_only_ability**: Intersection of request categories and human-only ability
-- **request::use_case**: Intersection of request categories and use case categories
-- **request::task_success**: Intersection of request categories and task success
-- **request::human_only_time**: Mean human-only time per request category
-- **request::human_with_ai_time**: Mean human-with-AI time per request category
-- **request::ai_autonomy**: Mean AI autonomy per request category
-- **request::human_education_years**: Mean human education years per request category
-- **request::ai_education_years**: Mean AI education years per request category
-- **request::cost**: Mean cost per request category (indexed, 1.0 = average)
-- **request::prompt_tokens**: Mean prompt tokens per request category (indexed, 1.0 = average)
-- **request::completion_tokens**: Mean completion tokens per request category (indexed, 1.0 = average)
-
-### Core Variables
-
-#### Content Facet Metrics
-**O*NET Task Metrics**:
-- **onet_task_count**: Number of 1P API records using this specific O*NET task
-- **onet_task_pct**: Percentage of total using this task
-
-**Request Metrics**:
-- **request_count**: Number of 1P API records in this request category
-- **request_pct**: Percentage of total in this category
-
-**Collaboration Pattern Metrics**:
-- **collaboration_count**: Number of 1P API records with this collaboration pattern
-- **collaboration_pct**: Percentage of total with this pattern
-
-**Multitasking Metrics**:
-- **multitasking_count**: Number of records with this multitasking status
-- **multitasking_pct**: Percentage of total with this status
-
-**Human-Only Ability Metrics**:
-- **human_only_ability_count**: Number of records with this human-only ability status
-- **human_only_ability_pct**: Percentage of total with this status
-
-**Use Case Metrics**:
-- **use_case_count**: Number of records in this use case category
-- **use_case_pct**: Percentage of total in this category
-
-**Task Success Metrics**:
-- **task_success_count**: Number of records with this task success status
-- **task_success_pct**: Percentage of total with this status
-
-#### Numeric Facet Metrics
-For numeric facets (human_only_time, human_with_ai_time, ai_autonomy, human_education_years, ai_education_years), the following distribution statistics are available:
-
-- **{facet}_mean**: Mean value across all records
-- **{facet}_median**: Median value across all records
-- **{facet}_stdev**: Standard deviation of values
-- **{facet}_mean_ci_lower**: Lower bound of 95% confidence interval for the mean
-- **{facet}_mean_ci_upper**: Upper bound of 95% confidence interval for the mean
-- **{facet}_median_ci_lower**: Lower bound of 95% confidence interval for the median
-- **{facet}_median_ci_upper**: Upper bound of 95% confidence interval for the median
-- **{facet}_count**: Total number of observations for this facet
-- **{facet}_histogram_count**: Count of observations in each histogram bin (one row per bin)
-- **{facet}_histogram_pct**: Percentage of observations in each histogram bin (one row per bin)
-
-#### Indexed Facet Metrics (API-specific)
-For indexed facets (cost_index, prompt_tokens_index, completion_tokens_index), values are normalized so that 1.0 represents the average:
-
-- **{facet}_index**: Re-indexed mean value (1.0 = average across all categories)
-- **{facet}_count**: Number of records for this metric
-
-#### Intersection Metrics
-For categorical intersections (e.g., onet_task::collaboration):
-- **{base}_{secondary}_count**: Records with both this base category and secondary category
-- **{base}_{secondary}_pct**: Percentage of the base category's total with this secondary category
-
-For numeric intersections (e.g., onet_task::human_only_time):
-- **{base}_{numeric}_mean**: Mean value for this category
-- **{base}_{numeric}_median**: Median value for this category
-- **{base}_{numeric}_stdev**: Standard deviation for this category
-- **{base}_{numeric}_count**: Number of observations for this category
-- **{base}_{numeric}_mean_ci_lower/upper**: 95% CI bounds for the mean
-- **{base}_{numeric}_median_ci_lower/upper**: 95% CI bounds for the median
-
-## External Data Sources
-
-We use external data to enrich Claude usage data with external economic and demographic sources.
-
-### ISO Country Codes
-
-**ISO 3166 Country Codes**
-
-International standard codes for representing countries and territories, used for mapping IP-based geolocation data to standardized country identifiers.
-
-- **Standard**: ISO 3166-1
-- **Source**: GeoNames geographical database
-- **URL**: https://download.geonames.org/export/dump/countryInfo.txt
-- **License**: Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)
-- **Attribution note**: Data in the data/intermediate and data/output folders have been processed and modified from original source; modifications to data in data/intermediate include extracting only tabular data, selecting a subset of columns, and renaming columns; modifications to data in data/output include transforming data to long format
-- **Download date**: September 2, 2025
-- **Output files**:
-  - `geonames_countryInfo.txt` (raw GeoNames data in data/input/)
-  - `iso_country_codes.csv` (processed country codes in data/intermediate/)
-- **Key fields**:
-  - `iso_alpha_2`: Two-letter country code (e.g., "US", "GB", "FR")
-  - `iso_alpha_3`: Three-letter country code (e.g., "USA", "GBR", "FRA")
-  - `country_name`: Country name from GeoNames
-- **Usage**: Maps IP-based country identification to standardized ISO codes for consistent geographic aggregation
-
-### ISO Region Code Mapping
-
+# Data Documentation
+
+This document describes the data sources and variables used in the fourth Anthropic Economic Index (AEI) report.
+
+## Claude.ai Usage Data
+
+### Overview
+The core dataset contains Claude.ai usage metrics aggregated by geography and analysis dimensions (facets).
+
+**Source files**:
+- `aei_raw_claude_ai_2025-11-13_to_2025-11-20.csv` (pre-enrichment data in data/intermediate/)
+
+**Note on data sources**: The AEI raw file contains raw counts and percentages.
+
+### Data Schema
+Each row represents one metric value for a specific geography and facet combination:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `geo_id` | string | Geographic identifier (ISO-3166-1 country code for countries, ISO 3166-2 region code for country-state, or "GLOBAL"). Examples: "USA", "AGO-LUA" (Angola-Luanda), "ALB-02" (Albania-Fier) (raw version uses 2- instead of 3-letter country codes) |
+| `geography` | string | Geographic level: "country", "country-state", or "global" |
+| `date_start` | date | Start of data collection period |
+| `date_end` | date | End of data collection period |
+| `platform_and_product` | string | "Claude AI (Free and Pro)" |
+| `facet` | string | Analysis dimension (see Facets below) |
+| `level` | integer | Sub-level within facet (0-2) |
+| `variable` | string | Metric name (see Variables below) |
+| `cluster_name` | string | Specific entity within facet (task, pattern, etc.). For intersections, format is "base::category" |
+| `value` | float | Numeric metric value |
+
+### Facets
+
+**Geographic Facets:**
+- **country**: Country-level aggregations
+- **country-state**: Subnational region aggregations (ISO 3166-2 regions globally)
+
+**Content Facets:**
+- **onet_task**: O*NET occupational tasks
+- **collaboration**: Human-AI collaboration patterns
+- **request**: Request complexity levels (0=highest granularity, 1=middle granularity, 2=lowest granularity)
+- **multitasking**: Whether conversation involves single or multiple tasks
+- **human_only_ability**: Whether a human could complete the task without AI assistance
+- **use_case**: Use case categories (work, coursework, personal)
+- **task_success**: Whether the task was successfully completed
+
+**Numeric Facets** (continuous variables with distribution statistics):
+- **human_only_time**: Estimated time for a human to complete the task without AI
+- **human_with_ai_time**: Estimated time for a human to complete the task with AI assistance
+- **ai_autonomy**: Degree of AI autonomy in task completion
+- **human_education_years**: Estimated years of human education required for the task
+- **ai_education_years**: Estimated equivalent years of AI "education" demonstrated
+
+**Intersection Facets:**
+- **onet_task::collaboration**: Intersection of O*NET tasks and collaboration patterns
+- **onet_task::multitasking**: Intersection of O*NET tasks and multitasking status
+- **onet_task::human_only_ability**: Intersection of O*NET tasks and human-only ability
+- **onet_task::use_case**: Intersection of O*NET tasks and use case categories
+- **onet_task::task_success**: Intersection of O*NET tasks and task success
+- **onet_task::human_only_time**: Mean human-only time per O*NET task
+- **onet_task::human_with_ai_time**: Mean human-with-AI time per O*NET task
+- **onet_task::ai_autonomy**: Mean AI autonomy per O*NET task
+- **onet_task::human_education_years**: Mean human education years per O*NET task
+- **onet_task::ai_education_years**: Mean AI education years per O*NET task
+- **request::collaboration**: Intersection of request categories and collaboration patterns
+- **request::multitasking**: Intersection of request categories and multitasking status
+- **request::human_only_ability**: Intersection of request categories and human-only ability
+- **request::use_case**: Intersection of request categories and use case categories
+- **request::task_success**: Intersection of request categories and task success
+- **request::human_only_time**: Mean human-only time per request category
+- **request::human_with_ai_time**: Mean human-with-AI time per request category
+- **request::ai_autonomy**: Mean AI autonomy per request category
+- **request::human_education_years**: Mean human education years per request category
+- **request::ai_education_years**: Mean AI education years per request category
+
+### Core Variables
+
+Variables follow the pattern `{prefix}_{suffix}` with specific meanings:
+
+**From AEI raw file**: `*_count`, `*_pct`
+
+#### Usage Metrics
+- **usage_count**: Total number of conversations/interactions in a geography
+- **usage_pct**: Percentage of total usage (relative to parent geography - global for countries, parent country for country-state regions)
+
+#### Content Facet Metrics
+**O*NET Task Metrics**:
+- **onet_task_count**: Number of conversations using this specific O*NET task
+- **onet_task_pct**: Percentage of geographic total using this task
+- **onet_task_pct_index**: Specialization index comparing task usage to baseline (global for countries, parent country for country-state regions)
+- **onet_task_collaboration_count**: Number of conversations with both this task and collaboration pattern (intersection)
+- **onet_task_collaboration_pct**: Percentage of the base task's total that has this collaboration pattern (sums to 100% within each task)
+
+#### Occupation Metrics
+- **soc_pct**: Percentage of classified O*NET tasks associated with this SOC major occupation group (e.g., Management, Computer and Mathematical)
+
+**Request Metrics**:
+- **request_count**: Number of conversations in this request category level
+- **request_pct**: Percentage of geographic total in this category
+- **request_collaboration_count**: Number of conversations with both this request category and collaboration pattern (intersection)
+- **request_collaboration_pct**: Percentage of the base request's total that has this collaboration pattern (sums to 100% within each request)
+
+**Collaboration Pattern Metrics**:
+- **collaboration_count**: Number of conversations with this collaboration pattern
+- **collaboration_pct**: Percentage of geographic total with this pattern
+
+**Multitasking Metrics**:
+- **multitasking_count**: Number of conversations with this multitasking status
+- **multitasking_pct**: Percentage of geographic total with this status
+
+**Human-Only Ability Metrics**:
+- **human_only_ability_count**: Number of conversations with this human-only ability status
+- **human_only_ability_pct**: Percentage of geographic total with this status
+
+**Use Case Metrics**:
+- **use_case_count**: Number of conversations in this use case category
+- **use_case_pct**: Percentage of geographic total in this category
+
+**Task Success Metrics**:
+- **task_success_count**: Number of conversations with this task success status
+- **task_success_pct**: Percentage of geographic total with this status
+
+#### Numeric Facet Metrics
+For numeric facets (human_only_time, human_with_ai_time, ai_autonomy, human_education_years, ai_education_years), the following distribution statistics are available:
+
+- **{facet}_mean**: Mean value across all conversations
+- **{facet}_median**: Median value across all conversations
+- **{facet}_stdev**: Standard deviation of values
+- **{facet}_mean_ci_lower**: Lower bound of 95% confidence interval for the mean
+- **{facet}_mean_ci_upper**: Upper bound of 95% confidence interval for the mean
+- **{facet}_median_ci_lower**: Lower bound of 95% confidence interval for the median
+- **{facet}_median_ci_upper**: Upper bound of 95% confidence interval for the median
+- **{facet}_count**: Total number of observations for this facet
+- **{facet}_histogram_count**: Count of observations in each histogram bin (one row per bin, bin range in cluster_name, e.g., "[1.0, 1.0)")
+- **{facet}_histogram_pct**: Percentage of observations in each histogram bin (one row per bin)
+
+For numeric intersection facets (e.g., onet_task::human_only_time), the same metrics are available per category (e.g., per O*NET task), with cluster_name containing the category identifier:
+- **{base}_{numeric}_mean**: Mean value for this category
+- **{base}_{numeric}_median**: Median value for this category
+- **{base}_{numeric}_stdev**: Standard deviation for this category
+- **{base}_{numeric}_count**: Number of observations for this category
+- **{base}_{numeric}_mean_ci_lower/upper**: 95% CI bounds for the mean
+- **{base}_{numeric}_median_ci_lower/upper**: 95% CI bounds for the median
+
+#### Special Values
+- **not_classified**: Indicates data that was filtered for privacy protection or could not be classified
+- **none**: Indicates the absence of the attribute (e.g., no collaboration, no task selected)
+
+### Data Processing Notes
+- **Minimum Observations**: 200 conversations per country, 100 per country-state region (applied in enrichment step, not raw preprocessing)
+- **not_classified**:
+  - For regular facets: Captures filtered/unclassified conversations
+  - For intersection facets: Each base cluster has its own not_classified (e.g., "task1::not_classified")
+- **Intersection Percentages**: Calculated relative to base cluster totals, ensuring each base cluster's percentages sum to 100%
+- **Country Codes**: ISO-3166-1 format for countries, three letter codes in the enriched file (e.g., "USA", "GBR", "FRA") and two letter codes in the raw file (e.g., "US", "GB", "FR"); ISO 3166-2 format for country-state regions (e.g., "AGO-LUA", "ALB-02" in enriched file, or "US-CA" in raw file)
+- **Variable Definitions**: See Core Variables section above
+
+## 1P API Usage Data
+
+### Overview
+Dataset containing first-party API usage metrics along various dimensions based on a sample of 1P API traffic and analyzed using privacy-preserving methods.
+
+**Note**: Unlike Claude.ai data, API data has **no geographic breakdowns** (no country or country-state facets). All API metrics are reported at global level only (`geography: "global"`, `geo_id: "GLOBAL"`).
+
+**Source file**: `aei_raw_1p_api_2025-11-13_to_2025-11-20.csv` (in data/intermediate/)
+
+### Data Schema
+Each row represents one metric value for a specific facet combination at global level:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `geo_id` | string | Geographic identifier (always "GLOBAL" for API data) |
+| `geography` | string | Geographic level (always "global" for API data) |
+| `date_start` | date | Start of data collection period |
+| `date_end` | date | End of data collection period |
+| `platform_and_product` | string | "1P API" |
+| `facet` | string | Analysis dimension (see Facets below) |
+| `level` | integer | Sub-level within facet (0-2) |
+| `variable` | string | Metric name (see Variables below) |
+| `cluster_name` | string | Specific entity within facet. For intersections, format is "base::category" or "base::index"/"base::count" for mean value metrics |
+| `value` | float | Numeric metric value |
+
+### Facets
+
+**Content Facets:**
+- **onet_task**: O*NET occupational tasks
+- **collaboration**: Human-AI collaboration patterns
+- **request**: Request categories (hierarchical levels 0-2 from bottom-up taxonomy)
+- **multitasking**: Whether conversation involves single or multiple tasks
+- **human_only_ability**: Whether a human could complete the task without AI assistance
+- **use_case**: Use case categories (work, coursework, personal)
+- **task_success**: Whether the task was successfully completed
+
+**Numeric Facets** (continuous variables with distribution statistics):
+- **human_only_time**: Estimated time for a human to complete the task without AI
+- **human_with_ai_time**: Estimated time for a human to complete the task with AI assistance
+- **ai_autonomy**: Degree of AI autonomy in task completion
+- **human_education_years**: Estimated years of human education required for the task
+- **ai_education_years**: Estimated equivalent years of AI "education" demonstrated
+
+**Intersection Facets:**
+- **onet_task::collaboration**: Intersection of O*NET tasks and collaboration patterns
+- **onet_task::multitasking**: Intersection of O*NET tasks and multitasking status
+- **onet_task::human_only_ability**: Intersection of O*NET tasks and human-only ability
+- **onet_task::use_case**: Intersection of O*NET tasks and use case categories
+- **onet_task::task_success**: Intersection of O*NET tasks and task success
+- **onet_task::human_only_time**: Mean human-only time per O*NET task
+- **onet_task::human_with_ai_time**: Mean human-with-AI time per O*NET task
+- **onet_task::ai_autonomy**: Mean AI autonomy per O*NET task
+- **onet_task::human_education_years**: Mean human education years per O*NET task
+- **onet_task::ai_education_years**: Mean AI education years per O*NET task
+- **onet_task::cost**: Mean cost per O*NET task (indexed, 1.0 = average)
+- **onet_task::prompt_tokens**: Mean prompt tokens per O*NET task (indexed, 1.0 = average)
+- **onet_task::completion_tokens**: Mean completion tokens per O*NET task (indexed, 1.0 = average)
+- **request::collaboration**: Intersection of request categories and collaboration patterns
+- **request::multitasking**: Intersection of request categories and multitasking status
+- **request::human_only_ability**: Intersection of request categories and human-only ability
+- **request::use_case**: Intersection of request categories and use case categories
+- **request::task_success**: Intersection of request categories and task success
+- **request::human_only_time**: Mean human-only time per request category
+- **request::human_with_ai_time**: Mean human-with-AI time per request category
+- **request::ai_autonomy**: Mean AI autonomy per request category
+- **request::human_education_years**: Mean human education years per request category
+- **request::ai_education_years**: Mean AI education years per request category
+- **request::cost**: Mean cost per request category (indexed, 1.0 = average)
+- **request::prompt_tokens**: Mean prompt tokens per request category (indexed, 1.0 = average)
+- **request::completion_tokens**: Mean completion tokens per request category (indexed, 1.0 = average)
+
+### Core Variables
+
+#### Content Facet Metrics
+**O*NET Task Metrics**:
+- **onet_task_count**: Number of 1P API records using this specific O*NET task
+- **onet_task_pct**: Percentage of total using this task
+
+**Request Metrics**:
+- **request_count**: Number of 1P API records in this request category
+- **request_pct**: Percentage of total in this category
+
+**Collaboration Pattern Metrics**:
+- **collaboration_count**: Number of 1P API records with this collaboration pattern
+- **collaboration_pct**: Percentage of total with this pattern
+
+**Multitasking Metrics**:
+- **multitasking_count**: Number of records with this multitasking status
+- **multitasking_pct**: Percentage of total with this status
+
+**Human-Only Ability Metrics**:
+- **human_only_ability_count**: Number of records with this human-only ability status
+- **human_only_ability_pct**: Percentage of total with this status
+
+**Use Case Metrics**:
+- **use_case_count**: Number of records in this use case category
+- **use_case_pct**: Percentage of total in this category
+
+**Task Success Metrics**:
+- **task_success_count**: Number of records with this task success status
+- **task_success_pct**: Percentage of total with this status
+
+#### Numeric Facet Metrics
+For numeric facets (human_only_time, human_with_ai_time, ai_autonomy, human_education_years, ai_education_years), the following distribution statistics are available:
+
+- **{facet}_mean**: Mean value across all records
+- **{facet}_median**: Median value across all records
+- **{facet}_stdev**: Standard deviation of values
+- **{facet}_mean_ci_lower**: Lower bound of 95% confidence interval for the mean
+- **{facet}_mean_ci_upper**: Upper bound of 95% confidence interval for the mean
+- **{facet}_median_ci_lower**: Lower bound of 95% confidence interval for the median
+- **{facet}_median_ci_upper**: Upper bound of 95% confidence interval for the median
+- **{facet}_count**: Total number of observations for this facet
+- **{facet}_histogram_count**: Count of observations in each histogram bin (one row per bin)
+- **{facet}_histogram_pct**: Percentage of observations in each histogram bin (one row per bin)
+
+#### Indexed Facet Metrics (API-specific)
+For indexed facets (cost_index, prompt_tokens_index, completion_tokens_index), values are normalized so that 1.0 represents the average:
+
+- **{facet}_index**: Re-indexed mean value (1.0 = average across all categories)
+- **{facet}_count**: Number of records for this metric
+
+#### Intersection Metrics
+For categorical intersections (e.g., onet_task::collaboration):
+- **{base}_{secondary}_count**: Records with both this base category and secondary category
+- **{base}_{secondary}_pct**: Percentage of the base category's total with this secondary category
+
+For numeric intersections (e.g., onet_task::human_only_time):
+- **{base}_{numeric}_mean**: Mean value for this category
+- **{base}_{numeric}_median**: Median value for this category
+- **{base}_{numeric}_stdev**: Standard deviation for this category
+- **{base}_{numeric}_count**: Number of observations for this category
+- **{base}_{numeric}_mean_ci_lower/upper**: 95% CI bounds for the mean
+- **{base}_{numeric}_median_ci_lower/upper**: 95% CI bounds for the median
+
+## External Data Sources
+
+We use external data to enrich Claude usage data with external economic and demographic sources.
+
+### ISO Country Codes
+
+**ISO 3166 Country Codes**
+
+International standard codes for representing countries and territories, used for mapping IP-based geolocation data to standardized country identifiers.
+
+- **Standard**: ISO 3166-1
+- **Source**: GeoNames geographical database
+- **URL**: https://download.geonames.org/export/dump/countryInfo.txt
+- **License**: Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)
+- **Attribution note**: Data in the data/intermediate and data/output folders have been processed and modified from original source; modifications to data in data/intermediate include extracting only tabular data, selecting a subset of columns, and renaming columns; modifications to data in data/output include transforming data to long format
+- **Download date**: September 2, 2025
+- **Output files**:
+  - `geonames_countryInfo.txt` (raw GeoNames data in data/input/)
+  - `iso_country_codes.csv` (processed country codes in data/intermediate/)
+- **Key fields**:
+  - `iso_alpha_2`: Two-letter country code (e.g., "US", "GB", "FR")
+  - `iso_alpha_3`: Three-letter country code (e.g., "USA", "GBR", "FRA")
+  - `country_name`: Country name from GeoNames
+- **Usage**: Maps IP-based country identification to standardized ISO codes for consistent geographic aggregation
+
+### ISO Region Code Mapping
+
 Region-level geographic data uses ISO 3166-2 standard subdivision codes. Some countries were excluded from region-level analysis due to mapping issues between source data codes and ISO 3166-2 standards. Country-level data remains available for all countries.

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-# Data Documentation
-
-This document describes the data sources and variables used in the fifth Anthropic Economic Index (AEI) report.
-
-## Claude.ai Usage Data
-
-### Overview
-The core dataset contains Claude.ai usage metrics aggregated by geography and analysis dimensions (facets).
-
-**Source files**:
-- `aei_raw_claude_ai_2026-02-05_to_2026-02-12.csv` 
-
-**Note on data sources**: The AEI raw file contains raw counts and percentages.
-
-### Data Schema
-Each row represents one metric value for a specific geography and facet combination:
-
-| Column | Type | Description |
-|--------|------|-------------|
-| `geo_id` | string | Geographic identifier (ISO-3166-1 country code for countries, ISO 3166-2 region code for country-state, or "GLOBAL"). Examples: "USA", "AGO-LUA" (Angola-Luanda), "ALB-02" (Albania-Fier) (raw version uses 2- instead of 3-letter country codes) |
-| `geography` | string | Geographic level: "country", "country-state", or "global" |
-| `date_start` | date | Start of data collection period |
-| `date_end` | date | End of data collection period |
-| `platform_and_product` | string | "Claude AI (Free, Pro, and Max)" |
-| `facet` | string | Analysis dimension (see Facets below) |
-| `level` | integer | Sub-level within facet (0-2) |
-| `variable` | string | Metric name (see Variables below) |
-| `cluster_name` | string | Specific entity within facet (task, pattern, etc.). For intersections, format is "base::category" |
-| `value` | float | Numeric metric value |
-
-### Facets
-
-**Geographic Facets:**
-- **country**: Country-level aggregations
-- **country-state**: Subnational region aggregations (ISO 3166-2 regions globally)
-
-**Content Facets:**
-- **onet_task**: O*NET occupational tasks
-- **collaboration**: Human-AI collaboration patterns
-- **request**: Request complexity levels (0=highest granularity, 1=middle granularity, 2=lowest granularity)
-- **multitasking**: Whether conversation involves single or multiple tasks
-- **human_only_ability**: Whether a human could complete the task without AI assistance
-- **use_case**: Use case categories (work, coursework, personal)
-- **task_success**: Whether the task was successfully completed
-
-**Numeric Facets** (continuous variables with distribution statistics):
-- **human_only_time**: Estimated time for a human to complete the task without AI
-- **human_with_ai_time**: Estimated time for a human to complete the task with AI assistance
-- **ai_autonomy**: Degree of AI autonomy in task completion
-- **human_education_years**: Estimated years of human education required for the task
-- **ai_education_years**: Estimated equivalent years of AI "education" demonstrated
-
-**Intersection Facets:**
-- **onet_task::collaboration**: Intersection of O*NET tasks and collaboration patterns
-- **onet_task::multitasking**: Intersection of O*NET tasks and multitasking status
-- **onet_task::human_only_ability**: Intersection of O*NET tasks and human-only ability
-- **onet_task::use_case**: Intersection of O*NET tasks and use case categories
-- **onet_task::task_success**: Intersection of O*NET tasks and task success
-- **onet_task::human_only_time**: Mean human-only time per O*NET task
-- **onet_task::human_with_ai_time**: Mean human-with-AI time per O*NET task
-- **onet_task::ai_autonomy**: Mean AI autonomy per O*NET task
-- **onet_task::human_education_years**: Mean human education years per O*NET task
-- **onet_task::ai_education_years**: Mean AI education years per O*NET task
-- **request::collaboration**: Intersection of request categories and collaboration patterns
-- **request::multitasking**: Intersection of request categories and multitasking status
-- **request::human_only_ability**: Intersection of request categories and human-only ability
-- **request::use_case**: Intersection of request categories and use case categories
-- **request::task_success**: Intersection of request categories and task success
-- **request::human_only_time**: Mean human-only time per request category
-- **request::human_with_ai_time**: Mean human-with-AI time per request category
-- **request::ai_autonomy**: Mean AI autonomy per request category
-- **request::human_education_years**: Mean human education years per request category
-- **request::ai_education_years**: Mean AI education years per request category
-
-### Core Variables
-
-Variables follow the pattern `{prefix}_{suffix}` with specific meanings:
-
-**From AEI raw file**: `*_count`, `*_pct`
-
-#### Usage Metrics
-- **usage_count**: Total number of conversations/interactions in a geography
-- **usage_pct**: Percentage of total usage (relative to parent geography - global for countries, parent country for country-state regions)
-
-#### Content Facet Metrics
-**O*NET Task Metrics**:
-- **onet_task_count**: Number of conversations using this specific O*NET task
-- **onet_task_pct**: Percentage of geographic total using this task
-- **onet_task_collaboration_count**: Number of conversations with both this task and collaboration pattern (intersection)
-- **onet_task_collaboration_pct**: Percentage of the base task's total that has this collaboration pattern (sums to 100% within each task)
-
-**Request Metrics**:
-- **request_count**: Number of conversations in this request category level
-- **request_pct**: Percentage of geographic total in this category
-- **request_collaboration_count**: Number of conversations with both this request category and collaboration pattern (intersection)
-- **request_collaboration_pct**: Percentage of the base request's total that has this collaboration pattern (sums to 100% within each request)
-
-**Collaboration Pattern Metrics**:
-- **collaboration_count**: Number of conversations with this collaboration pattern
-- **collaboration_pct**: Percentage of geographic total with this pattern
-
-**Multitasking Metrics**:
-- **multitasking_count**: Number of conversations with this multitasking status
-- **multitasking_pct**: Percentage of geographic total with this status
-
-**Human-Only Ability Metrics**:
-- **human_only_ability_count**: Number of conversations with this human-only ability status
-- **human_only_ability_pct**: Percentage of geographic total with this status
-
-**Use Case Metrics**:
-- **use_case_count**: Number of conversations in this use case category
-- **use_case_pct**: Percentage of geographic total in this category
-
-**Task Success Metrics**:
-- **task_success_count**: Number of conversations with this task success status
-- **task_success_pct**: Percentage of geographic total with this status
-
-#### Numeric Facet Metrics
-For numeric facets (human_only_time, human_with_ai_time, ai_autonomy, human_education_years, ai_education_years), the following distribution statistics are available:
-
-- **{facet}_mean**: Mean value across all conversations
-- **{facet}_median**: Median value across all conversations
-- **{facet}_stdev**: Standard deviation of values
-- **{facet}_mean_ci_lower**: Lower bound of 95% confidence interval for the mean
-- **{facet}_mean_ci_upper**: Upper bound of 95% confidence interval for the mean
-- **{facet}_median_ci_lower**: Lower bound of 95% confidence interval for the median
-- **{facet}_median_ci_upper**: Upper bound of 95% confidence interval for the median
-- **{facet}_count**: Total number of observations for this facet
-- **{facet}_histogram_count**: Count of observations in each histogram bin (one row per bin, bin range in cluster_name, e.g., "[1.0, 1.0)")
-- **{facet}_histogram_pct**: Percentage of observations in each histogram bin (one row per bin)
-
-For numeric intersection facets (e.g., onet_task::human_only_time), the same metrics are available per category (e.g., per O*NET task), with cluster_name containing the category identifier:
-- **{base}_{numeric}_mean**: Mean value for this category
-- **{base}_{numeric}_median**: Median value for this category
-- **{base}_{numeric}_stdev**: Standard deviation for this category
-- **{base}_{numeric}_count**: Number of observations for this category
-- **{base}_{numeric}_mean_ci_lower/upper**: 95% CI bounds for the mean
-- **{base}_{numeric}_median_ci_lower/upper**: 95% CI bounds for the median
-
-#### Special Values
-- **not_classified**: Indicates data that was filtered for privacy protection or could not be classified
-- **none**: Indicates the absence of the attribute (e.g., no collaboration, no task selected)
-
-### Data Processing Notes
-- **not_classified**:
-  - For regular facets: Captures filtered/unclassified conversations
-  - For intersection facets: Each base cluster has its own not_classified (e.g., "task1::not_classified")
-- **Intersection Percentages**: Calculated relative to base cluster totals, ensuring each base cluster's percentages sum to 100%
-- **Country Codes**: ISO-3166-1 format for countries, two letter codes in the raw file (e.g., "US", "GB", "FR"); ISO 3166-2 format for country-state regions (e.g. "US-CA" in raw file)
-- **Variable Definitions**: See Core Variables section above
-
-## 1P API Usage Data
-
-### Overview
-Dataset containing first-party API usage metrics along various dimensions based on a sample of 1P API traffic and analyzed using privacy-preserving methods.
-
-**Note**: Unlike Claude.ai data, API data has **no geographic breakdowns** (no country or country-state facets). All API metrics are reported at global level only (`geography: "global"`, `geo_id: "GLOBAL"`).
-
-**Source file**: `aei_raw_1p_api_2026-02-05_to_2026-02-12.csv` 
-
-### Data Schema
-Each row represents one metric value for a specific facet combination at global level:
-
-| Column | Type | Description |
-|--------|------|-------------|
-| `geo_id` | string | Geographic identifier (always "GLOBAL" for API data) |
-| `geography` | string | Geographic level (always "global" for API data) |
-| `date_start` | date | Start of data collection period |
-| `date_end` | date | End of data collection period |
-| `platform_and_product` | string | "1P API" |
-| `facet` | string | Analysis dimension (see Facets below) |
-| `level` | integer | Sub-level within facet (0-2) |
-| `variable` | string | Metric name (see Variables below) |
-| `cluster_name` | string | Specific entity within facet. For intersections, format is "base::category" or "base::value" for mean value metrics |
-| `value` | float | Numeric metric value |
-
-### Facets
-
-**Content Facets:**
-- **onet_task**: O*NET occupational tasks
-- **collaboration**: Human-AI collaboration patterns
-- **request**: Request categories (hierarchical levels 0-2 from bottom-up taxonomy)
-- **multitasking**: Whether conversation involves single or multiple tasks
-- **human_only_ability**: Whether a human could complete the task without AI assistance
-- **use_case**: Use case categories (work, coursework, personal)
-- **task_success**: Whether the task was successfully completed
-
-**Numeric Facets** (continuous variables with distribution statistics):
-- **human_only_time**: Estimated time for a human to complete the task without AI
-- **human_with_ai_time**: Estimated time for a human to complete the task with AI assistance
-- **ai_autonomy**: Degree of AI autonomy in task completion
-- **human_education_years**: Estimated years of human education required for the task
-- **ai_education_years**: Estimated equivalent years of AI "education" demonstrated
-
-**Intersection Facets:**
-- **onet_task::collaboration**: Intersection of O*NET tasks and collaboration patterns
-- **onet_task::multitasking**: Intersection of O*NET tasks and multitasking status
-- **onet_task::human_only_ability**: Intersection of O*NET tasks and human-only ability
-- **onet_task::use_case**: Intersection of O*NET tasks and use case categories
-- **onet_task::task_success**: Intersection of O*NET tasks and task success
-- **onet_task::human_only_time**: Mean human-only time per O*NET task
-- **onet_task::human_with_ai_time**: Mean human-with-AI time per O*NET task
-- **onet_task::ai_autonomy**: Mean AI autonomy per O*NET task
-- **onet_task::human_education_years**: Mean human education years per O*NET task
-- **onet_task::ai_education_years**: Mean AI education years per O*NET task
-- **onet_task::cost**: Mean cost per O*NET task (indexed, 1.0 = average)
-- **onet_task::prompt_tokens**: Mean prompt tokens per O*NET task (indexed, 1.0 = average)
-- **onet_task::completion_tokens**: Mean completion tokens per O*NET task (indexed, 1.0 = average)
-- **request::collaboration**: Intersection of request categories and collaboration patterns
-- **request::multitasking**: Intersection of request categories and multitasking status
-- **request::human_only_ability**: Intersection of request categories and human-only ability
-- **request::use_case**: Intersection of request categories and use case categories
-- **request::task_success**: Intersection of request categories and task success
-- **request::human_only_time**: Mean human-only time per request category
-- **request::human_with_ai_time**: Mean human-with-AI time per request category
-- **request::ai_autonomy**: Mean AI autonomy per request category
-- **request::human_education_years**: Mean human education years per request category
-- **request::ai_education_years**: Mean AI education years per request category
-- **request::cost**: Mean cost per request category (indexed, 1.0 = average)
-- **request::prompt_tokens**: Mean prompt tokens per request category (indexed, 1.0 = average)
-- **request::completion_tokens**: Mean completion tokens per request category (indexed, 1.0 = average)
-
-### Core Variables
-
-#### Content Facet Metrics
-**O*NET Task Metrics**:
-- **onet_task_count**: Number of 1P API records using this specific O*NET task
-- **onet_task_pct**: Percentage of total using this task
-
-**Request Metrics**:
-- **request_count**: Number of 1P API records in this request category
-- **request_pct**: Percentage of total in this category
-
-**Collaboration Pattern Metrics**:
-- **collaboration_count**: Number of 1P API records with this collaboration pattern
-- **collaboration_pct**: Percentage of total with this pattern
-
-**Multitasking Metrics**:
-- **multitasking_count**: Number of records with this multitasking status
-- **multitasking_pct**: Percentage of total with this status
-
-**Human-Only Ability Metrics**:
-- **human_only_ability_count**: Number of records with this human-only ability status
-- **human_only_ability_pct**: Percentage of total with this status
-
-**Use Case Metrics**:
-- **use_case_count**: Number of records in this use case category
-- **use_case_pct**: Percentage of total in this category
-
-**Task Success Metrics**:
-- **task_success_count**: Number of records with this task success status
-- **task_success_pct**: Percentage of total with this status
-
-#### Numeric Facet Metrics
-For numeric facets (human_only_time, human_with_ai_time, ai_autonomy, human_education_years, ai_education_years), the following distribution statistics are available:
-
-- **{facet}_mean**: Mean value across all records
-- **{facet}_median**: Median value across all records
-- **{facet}_stdev**: Standard deviation of values
-- **{facet}_mean_ci_lower**: Lower bound of 95% confidence interval for the mean
-- **{facet}_mean_ci_upper**: Upper bound of 95% confidence interval for the mean
-- **{facet}_median_ci_lower**: Lower bound of 95% confidence interval for the median
-- **{facet}_median_ci_upper**: Upper bound of 95% confidence interval for the median
-- **{facet}_count**: Total number of observations for this facet
-- **{facet}_histogram_count**: Count of observations in each histogram bin (one row per bin)
-- **{facet}_histogram_pct**: Percentage of observations in each histogram bin (one row per bin)
-
-#### Indexed Facet Metrics (API-specific)
-For indexed facets (cost_index, prompt_tokens_index, completion_tokens_index), values are normalized so that 1.0 represents the average:
-
-- **{facet}_index**: Re-indexed mean value (1.0 = average across all categories)
-- **{facet}_count**: Number of records for this metric
-
-#### Intersection Metrics
-For categorical intersections (e.g., onet_task::collaboration):
-- **{base}_{secondary}_count**: Records with both this base category and secondary category
-- **{base}_{secondary}_pct**: Percentage of the base category's total with this secondary category
-
-For numeric intersections (e.g., onet_task::human_only_time):
-- **{base}_{numeric}_mean**: Mean value for this category
-- **{base}_{numeric}_median**: Median value for this category
-- **{base}_{numeric}_stdev**: Standard deviation for this category
-- **{base}_{numeric}_count**: Number of observations for this category
-- **{base}_{numeric}_mean_ci_lower/upper**: 95% CI bounds for the mean
-- **{base}_{numeric}_median_ci_lower/upper**: 95% CI bounds for the median
-
-## External Data Sources
-
-We use external data to enrich Claude usage data with external economic and demographic sources.
-
-### ISO Country Codes
-
-**ISO 3166 Country Codes**
-
-International standard codes for representing countries and territories, used for mapping IP-based geolocation data to standardized country identifiers.
-
-- **Standard**: ISO 3166-1
-- **Source**: GeoNames geographical database
-- **URL**: https://download.geonames.org/export/dump/countryInfo.txt
-- **License**: Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)
-- **Download date**: September 2, 2025
-- **Key fields**:
-  - `iso_alpha_2`: Two-letter country code (e.g., "US", "GB", "FR")
-  - `iso_alpha_3`: Three-letter country code (e.g., "USA", "GBR", "FRA")
-  - `country_name`: Country name from GeoNames
-- **Usage**: Maps IP-based country identification to standardized ISO codes for consistent geographic aggregation
-
-### ISO Region Code Mapping
-
-Region-level geographic data uses ISO 3166-2 standard subdivision codes. Some countries were excluded from region-level analysis due to mapping issues between source data codes and ISO 3166-2 standards. Country-level data remains available for all countries.

release_2026_06_26/data/aei_1p_api_2026-06-26.csv

@@ -1,3 +0,0 @@
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-size 77282477

release_2026_06_26/data/aei_claude_ai_2026-06-26.csv

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-size 219174671

release_2026_06_26/data_documentation.md

@@ -1,110 +0,0 @@
-# Anthropic Economic Index Data Documentation
-
-This documentation outlines the data files, schema, and variables for this release of the Anthropic Economic Index. The core dataset contains Claude usage metrics aggregated by geography and analysis dimensions (categories) on a calendar-month basis. This release includes data for April and May 2026, with future release schedules to be announced.
-
-## Source Files
-
-| File | `source_id` | Description | Breakdowns by Geography |
-| :---- | :---- | :---- | :---- |
-| `aei_claude_ai_<date>.csv` | `claude_ai` | Claude chat and Cowork (Free, Pro, and Max plans) | global, country, subregion |
-| `aei_1p_api_<date>.csv` | `1p_api` | Anthropic 1P API calls, excluding Claude Code. | global only |
-
-## Data Schema
-
-Each row represents one metric value for a specific geography and category combination.
-
-| Column | Type | Description |
-| :---- | :---- | :---- |
-| `date_start` | date | Start of data collection period (inclusive) |
-| `date_end` | date | End of data collection period (exclusive). |
-| `geo_id` | string | `GLOBAL`, an ISO 3166-1 alpha-3 country code, or an ISO 3166-2 subregion code. |
-| `geo_level` | string | `global`, `country`, or `subregion`. |
-| `category_name` | string | Analysis dimension (see Categories below) |
-| `hierarchy_level` | int | Hierarchy depth within the category. 0 is the most granular level. |
-| `metric_id` | string | Metric name (see supported metrics below) |
-| `value` | float | The published value, rounded to two decimal places. |
-| `node_name` | string | Specific entity within the category |
-| `node_external_id` | string | Source identifier for the node: O\*NET element ID, SOC code, or request-topic UUID. |
-
-## Categories
-
-| `category_name` | Description | Level 0 (leaf) | Level 1 | Level 2 | Level 3 |
-| :---- | :---- | :---- | :---- | :---- | :---- |
-| `overall` | All conversations combined, with no topic or task breakdown. | Overall | — | — | — |
-| `onet` | Work activities defined by the U.S. Department of Labor's O\*NET database. | Task | Detailed Work Activity (DWA) | Intermediate Work Activity (IWA) | Generalized Work Activity (GWA) |
-| `request` | What requests users make to Claude, grouped into a topic hierarchy. | Detailed | Minor | Major | — |
-| `soc_occupation` | Occupations from the U.S. Bureau of Labor Statistics' Standard Occupational Classification. | Detailed Occupation | Major Group | — | — |
-
-## Metric Availability
-
-| Source | Geography | Overall | O\*NET | Request | SOC | Metrics Included |
-| :---- | :---- | :---: | :---: | :---: | :---: | :---- |
-| `claude_ai` | Global | ✓ | ✓ | ✓ | ✓ | All Metrics |
-| `claude_ai` | Country | ✓ | — | — | — | All Metrics |
-| `claude_ai` | Country | — | ✓ | ✓ | ✓ | `pct` |
-| `claude_ai` | Country | — | GWA | Major | Major Group | All Metrics |
-| `claude_ai` | Subregion | ✓ | — | — | — | All Metrics |
-| `claude_ai` | Subregion | — | ✓ | ✓ | ✓ | `pct` |
-| `1p_api` | Global | ✓ | ✓ | ✓ | ✓ | All Metrics |
-
-A cell is only published if it meets both the aggregation thresholds and the geography sample floor for the given row. The geography sample floor is the minimum number of sampled conversations a geography must have in a period to publish metrics for the breakdowns defined in that row. `usage_per_capita_index` at the subregion grain is published only for US states. A missing row means the cell was not published, not necessarily that the value is zero.
-
-## Metrics
-
-| `metric_id` | Unit | Description |
-| :---- | :---- | :---- |
-| `usage_pct` | percent | Percentage of total usage (relative to parent geography: global for countries, parent country for subregions). |
-| `usage_per_capita_index` | index | Anthropic Usage Index - Usage share divided by working-age (15-64) population share. 1.0 means proportional to population. Countries and US states only. |
-| `pct` | percent | Percentage of the geography's total in this category node. |
-| `multitasking_pct` | percent | Multitasking status assigned to `yes` (the conversation involves more than one distinct task). |
-| `human_only_ability_pct` | percent | Human-only ability status assigned to `yes` (a human could complete the task without AI assistance). |
-| `ai_autonomy_mean` | 1-5 scale | Mean degree of AI autonomy in task completion. |
-| `ai_education_years_mean` | years | Mean estimated equivalent years of AI "education" demonstrated. |
-| `human_education_years_mean` | years | Mean estimated years of human education required for the task. |
-| `human_only_time_mean` | hours | Mean estimated time for a human to complete the task without AI. |
-| `human_with_ai_time_mean` | minutes | Mean estimated time for a human to complete the task with AI assistance. |
-| `use_case_work_pct` | percent | Use case category assigned to `work`. |
-| `use_case_personal_pct` | percent | Use case category assigned to `personal`. |
-| `use_case_coursework_pct` | percent | Use case category assigned to `coursework`. |
-| `collaboration_bucket_automation_pct` | percent | Human-AI collaboration bucket assigned to `automation`. |
-| `collaboration_bucket_augmentation_pct` | percent | Human-AI collaboration bucket assigned to `augmentation`. |
-| `collaboration_directive_pct` | percent | Human-AI collaboration pattern assigned to `directive`. |
-| `collaboration_feedback_loop_pct` | percent | Human-AI collaboration pattern assigned to `feedback_loop`. |
-| `collaboration_task_iteration_pct` | percent | Human-AI collaboration pattern assigned to `task_iteration`. |
-| `collaboration_learning_pct` | percent | Human-AI collaboration pattern assigned to `learning`. |
-| `collaboration_validation_pct` | percent | Human-AI collaboration pattern assigned to `validation`. |
-| `collaboration_none_pct` | percent | Human-AI collaboration pattern assigned to `none`. |
-| `artifact_{label}_pct` | percent | Artifact type assigned to `{label}`, defined as the most prominent concrete output Claude produced. One metric per label (see Artifact labels below). |
-
-## License
-
-Data released under CC-BY.
-
-## Contact
-
-For press inquiries, contact press@anthropic.com. For all other questions, reach out to econ-research@anthropic.com.
-
-## Citation
-
-```
-@online{anthropic2026aeiv6,
-        author = {Maxim Massenkoff and Eva Lyubich and Szymon Sacher and Zoe Hitzig and Shaoyi Zhang and Ryan Heller and Peter McCrory},
-        title = {Anthropic Economic Index report: Cadences},
-        date = {2026-06-26},
-        year = {2026},
-        url = {https://www.anthropic.com/research/economic-index-june-2026-report},
-}
-```
-
-## Artifact Labels
-
-| | | | |
-| :---- | :---- | :---- | :---- |
-| `academic_paper_or_thesis` | `advice_or_recommendation` | `analysis_or_summary` | `app_or_website` |
-| `audio_or_music` | `blog_or_article` | `chart_or_visualization` | `code_fix_or_debug` |
-| `config_or_infra` | `creative_writing` | `data_or_spreadsheet` | `document_or_report` |
-| `educational_material` | `email_or_message` | `explanation_or_answer` | `game_or_interactive` |
-| `idea_or_brainstorm` | `image_or_graphic` | `marketing_or_social_content` | `math_or_calculation` |
-| `ml_or_ai_system` | `none` | `other` | `plan_or_strategy` |
-| `presentation_or_slides` | `recipe_or_meal_plan` | `resume_or_job_application` | `script_or_snippet` |
-| `sql_or_database_query` | `translation` | `ui_or_design_mockup` | `video_or_animation` |

robot_exposure/README.md

@@ -1,141 +0,0 @@
-# Data description for "What work can robots do?"
-
-This file describes the data release accompanying "What work can robots do?". The data
-consist of task and occupation robot exposure ratings. Tasks come from the U.S. Department
-of Labor's O\*NET database. Claude Opus 5 (with web search) rated the O\*NET 29.3 tasks that
-were classified as physical, as of 2026.
-
-## Source Files
-
-| File | Unit of observation | Rows | Description |
-| :---- | :---- | ----: | :---- |
-| `robot_exposure_occupations.csv` | O\*NET occupation | 923 | The robot exposure index for each occupation. |
-| `robot_exposure_tasks.csv` | O\*NET task | 18,796 | The robot exposure rating for each task. |
-
-Both files are UTF-8 CSV with a header row. The two files join on `onetsoc_code`. Within
-the tasks file, (`onetsoc_code`, `task_id`) is unique. Numbers are rounded to 4
-decimal places.
-
-## Occupations File Schema
-
-Each row is one O\*NET 29.3 occupation with task statements. The 93 O\*NET-SOC
-codes without task statements (74 "All Other" codes and 19
-military occupations) are not included.
-
-| Column | Type | Description |
-| :---- | :---- | :---- |
-| `onetsoc_code` | string | O\*NET-SOC 2019 occupation code, for example `53-3054.00`. |
-| `occupation_title` | string | O\*NET occupation title. |
-| `robot_exposure_index` | float | Robot exposure index, 0 to 3. The average of the occupation's task scores (`E1` = 1, `E2` = 2, `E3` = 3, otherwise 0), weighting each task by its time share. |
-
-## Tasks File Schema
-
-Each row is one task of one occupation. All tasks are included.
-
-| Column | Type | Description |
-| :---- | :---- | :---- |
-| `onetsoc_code` | string | O\*NET-SOC 2019 occupation code. |
-| `occupation_title` | string | O\*NET occupation title. |
-| `task_id` | string | O\*NET task ID. |
-| `task_statement` | string | O\*NET task statement. |
-| `time_share` | float | Claude's estimate of the share of the occupation's working time spent on the task. Sums to 1 within each occupation, up to rounding. |
-| `physical` | string | `Yes` if the task is physical (see Physical Tasks below), else `No`. |
-| `exposure_tier` | string | Exposure tier of a physical task, `E0` to `E3` (see Exposure Tiers below). Empty if the task is not physical. |
-| `reasoning` | string | Claude's explanation of the task's tier. For a task Claude found not physical, why it is not physical. Empty for tasks that were not rated. |
-| `instances` | JSON list | The representative task instances Claude rated (see Task Instances below). |
-| `sources` | JSON list | The sources Claude cited (see Sources below). Empty for tasks that were not rated or that cite no source. |
-
-Up to rounding, an occupation's `robot_exposure_index` equals the sum over its rows of
-`time_share` times the score of `exposure_tier` (`E1` = 1, `E2` = 2, `E3` = 3; 0 for `E0`
-and for an empty tier).
-
-## Exposure Tiers
-
-Task exposure is rated by the kind of environment in which a robot could perform the task.
-Task exposure is the highest exposure level for which more than half of instances by weight
-are exposed at that level or higher.
-
-| `exposure_tier` | Score | Environment | Description | Tasks |
-| :---- | :---: | :---- | :---- | ----: |
-| `E0` | 0 | No environment | No cited system could complete the instance even in a purpose-built setting. | 2,419 |
-| `E1` | 1 | Purpose-built robotic work environment | A setting built for the machine: fixtures hold each workpiece in a known position, conveyors present inputs one way, fences or light curtains keep people out. Examples: a fenced machine-tending cell, a bottling line, an automotive paint booth. Mark of E1: the setting is built around the machine, not around people. | 3,967 |
-| `E2` | 2 | Structured human work facility | A setting built for human work and kept predictable: a fixed layout, standard equipment, and an institution that controls who and what is present. It may be indoor or outdoor. Examples: a hospital pharmacy, a hotel corridor, an airport concourse, a container port. Mark of E2: an institution controls the premises and keeps them to a working standard. | 1,103 |
-| `E3` | 3 | Unstructured environment | A setting taken as found: the layout differs site to site, novel objects appear, and conditions are not kept to any standard. Examples: a private home, a construction site, a public sidewalk. Mark of E3: no institution controls the setting or keeps it to a working standard. | 105 |
-
-## Physical Tasks
-
-Physical tasks are defined in Appendix A using task ratings on physical, cognitive, and
-interpersonal work. Exposure is rated for all of these tasks. In total, 7,594 tasks are
-physical; this number excludes 432 tasks for which exposure was rated but the exposure
-rating found that the task is not physical.
-
-## Task Instances
-
-`instances` is a JSON list with one object per instance.
-
-| Field | Type | Description |
-| :---- | :---- | :---- |
-| `instance` | int | Instance number within the task, from 0. |
-| `description` | string | Description of the task instance. |
-| `weight_pct` | int | Share of the task's occurrences, in percent (multiples of 5, summing to 100 within a task). |
-| `tier` | string | Highest tier at which a cited robot could complete the instance, `E0` to `E3`. |
-| `setting_tier` | string | Tier of the instance's setting. |
-| `environment` | string | The setting in which the decisive cited robot actually operates. |
-| `sources` | string | Cited `source` numbers for Claude's rating, comma-separated. |
-| `reasoning` | string | Claude's explanation of the instance's tier. |
-
-## Sources
-
-`sources` is a JSON list with one object per cited source.
-
-| Field | Type | Description |
-| :---- | :---- | :---- |
-| `source` | int | Source number within the task, from 0. |
-| `system` | string | The robot or robotic system. |
-| `developer` | string | Its developer. |
-| `date` | string | When the demonstration or deployment took place (may be approximate). |
-| `maturity` | string | `deployed`, `commercial`, or `demo`. |
-| `autonomy_status` | string | `autonomous`, `teleoperated`, or `unclear`. |
-| `claim` | string | Claude's claim about this source. |
-| `source_title` | string | Title of the source. |
-| `url` | string | URL of the source. |
-| `quote` | string | The first 5 words of the passage Claude quoted from the source. |
-| `transfer_justification` | string or null | Used when Claude cites a robot that performs a related task, to explain why it applies to this task. |
-
-The file holds 56,933 sources: 20,877 `deployed`, 25,743 `commercial`,
-and 10,313 `demo`.
-
-## Quotes
-
-Quotes from sources are cut to their first 5 words and end with "...". This
-applies to the `quote` field and to any passage of more than 5 words in
-quotation marks in the other text fields. O\*NET task statements and work activity titles
-are quoted in full. Claude's response text sometimes repeats a source's words without
-quotation marks; any string of more than 5 consecutive words that appears in a
-full source quote is cut from Claude's response text.
-
-## License
-
-Data released under CC BY 4.0.
-
-This release includes information from the O\*NET 29.3 Database by the U.S. Department of
-Labor, Employment and Training Administration (USDOL/ETA), used under the CC BY 4.0
-license. O\*NET® is a trademark of USDOL/ETA. Anthropic has modified all or some of this
-information. USDOL/ETA has not approved, endorsed, or tested these modifications.
-
-## Contact
-
-For press inquiries, contact press@anthropic.com. For all other questions, reach out to
-econ-research@anthropic.com.
-
-## Citation
-
-```
-@online{legateyang2026robots,
- author = {Legate-Yang, Russell and Massenkoff, Maxim},
- title = {What work can robots do?},
- date = {2026-09-30},
- year = {2026},
- url = {https://www.anthropic.com/research/what-work-can-robots-do}
-}
-```

robot_exposure/robot_exposure_occupations.csv

@@ -1,924 +0,0 @@
-onetsoc_code,occupation_title,robot_exposure_index
-11-1011.00,Chief Executives,0.0
-11-1011.03,Chief Sustainability Officers,0.0
-11-1021.00,General and Operations Managers,0.033
-11-1031.00,Legislators,0.0
-11-2011.00,Advertising and Promotions Managers,0.0
-11-2021.00,Marketing Managers,0.0
-11-2022.00,Sales Managers,0.0
-11-2032.00,Public Relations Managers,0.0
-11-2033.00,Fundraising Managers,0.0
-11-3012.00,Administrative Services Managers,0.0
-11-3013.00,Facilities Managers,0.0
-11-3013.01,Security Managers,0.0
-11-3021.00,Computer and Information Systems Managers,0.0
-11-3031.00,Financial Managers,0.0
-11-3031.01,Treasurers and Controllers,0.0119
-11-3031.03,Investment Fund Managers,0.0
-11-3051.00,Industrial Production Managers,0.0
-11-3051.01,Quality Control Systems Managers,0.0
-11-3051.02,Geothermal Production Managers,0.2174
-11-3051.03,Biofuels Production Managers,0.0112
-11-3051.04,Biomass Power Plant Managers,0.2222
-11-3051.06,Hydroelectric Production Managers,0.1628
-11-3061.00,Purchasing Managers,0.0
-11-3071.00,"Transportation, Storage, and Distribution Managers",0.0652
-11-3071.04,Supply Chain Managers,0.0
-11-3111.00,Compensation and Benefits Managers,0.0
-11-3121.00,Human Resources Managers,0.0
-11-3131.00,Training and Development Managers,0.0
-11-9013.00,"Farmers, Ranchers, and Other Agricultural Managers",0.6939
-11-9021.00,Construction Managers,0.0
-11-9031.00,"Education and Childcare Administrators, Preschool and Daycare",0.0
-11-9032.00,"Education Administrators, Kindergarten through Secondary",0.0
-11-9033.00,"Education Administrators, Postsecondary",0.0
-11-9041.00,Architectural and Engineering Managers,0.0
-11-9041.01,Biofuels/Biodiesel Technology and Product Development Managers,0.1728
-11-9051.00,Food Service Managers,0.3711
-11-9071.00,Gambling Managers,0.0465
-11-9072.00,"Entertainment and Recreation Managers, Except Gambling",0.2262
-11-9081.00,Lodging Managers,0.0538
-11-9111.00,Medical and Health Services Managers,0.0
-11-9121.00,Natural Sciences Managers,0.0
-11-9121.01,Clinical Research Coordinators,0.0625
-11-9121.02,Water Resource Specialists,0.1333
-11-9131.00,Postmasters and Mail Superintendents,0.069
-11-9141.00,"Property, Real Estate, and Community Association Managers",0.1333
-11-9151.00,Social and Community Service Managers,0.0
-11-9161.00,Emergency Management Directors,0.0115
-11-9171.00,Funeral Home Managers,0.0
-11-9179.01,Fitness and Wellness Coordinators,0.0
-11-9179.02,Spa Managers,0.0235
-11-9199.01,Regulatory Affairs Managers,0.0
-11-9199.02,Compliance Managers,0.0
-11-9199.08,Loss Prevention Managers,0.0
-11-9199.09,Wind Energy Operations Managers,0.0
-11-9199.10,Wind Energy Development Managers,0.0
-11-9199.11,Brownfield Redevelopment Specialists and Site Managers,0.1205
-13-1011.00,"Agents and Business Managers of Artists, Performers, and Athletes",0.0
-13-1021.00,"Buyers and Purchasing Agents, Farm Products",0.1778
-13-1022.00,"Wholesale and Retail Buyers, Except Farm Products",0.0
-13-1023.00,"Purchasing Agents, Except Wholesale, Retail, and Farm Products",0.0
-13-1031.00,"Claims Adjusters, Examiners, and Investigators",0.1
-13-1032.00,"Insurance Appraisers, Auto Damage",0.0
-13-1041.00,Compliance Officers,0.0
-13-1041.01,Environmental Compliance Inspectors,0.2692
-13-1041.03,Equal Opportunity Representatives and Officers,0.0
-13-1041.04,Government Property Inspectors and Investigators,0.5132
-13-1041.06,Coroners,0.0341
-13-1041.07,Regulatory Affairs Specialists,0.0
-13-1041.08,Customs Brokers,0.0
-13-1051.00,Cost Estimators,0.0723
-13-1071.00,Human Resources Specialists,0.0
-13-1074.00,Farm Labor Contractors,0.4545
-13-1075.00,Labor Relations Specialists,0.0
-13-1081.00,Logisticians,0.0
-13-1081.01,Logistics Engineers,0.0
-13-1081.02,Logistics Analysts,0.0
-13-1082.00,Project Management Specialists,0.0
-13-1111.00,Management Analysts,0.0
-13-1121.00,"Meeting, Convention, and Event Planners",0.0
-13-1131.00,Fundraisers,0.012
-13-1141.00,"Compensation, Benefits, and Job Analysis Specialists",0.0
-13-1151.00,Training and Development Specialists,0.0
-13-1161.00,Market Research Analysts and Marketing Specialists,0.0
-13-1161.01,Search Marketing Strategists,0.0
-13-1199.04,Business Continuity Planners,0.0
-13-1199.05,Sustainability Specialists,0.0
-13-1199.06,Online Merchants,0.2069
-13-1199.07,Security Management Specialists,0.0513
-13-2011.00,Accountants and Auditors,0.0241
-13-2022.00,Appraisers of Personal and Business Property,0.1667
-13-2023.00,Appraisers and Assessors of Real Estate,0.0886
-13-2031.00,Budget Analysts,0.0
-13-2041.00,Credit Analysts,0.0
-13-2051.00,Financial and Investment Analysts,0.0
-13-2052.00,Personal Financial Advisors,0.0
-13-2053.00,Insurance Underwriters,0.0
-13-2054.00,Financial Risk Specialists,0.0
-13-2061.00,Financial Examiners,0.0
-13-2071.00,Credit Counselors,0.0
-13-2072.00,Loan Officers,0.0
-13-2081.00,"Tax Examiners and Collectors, and Revenue Agents",0.0
-13-2082.00,Tax Preparers,0.0
-13-2099.01,Financial Quantitative Analysts,0.0
-13-2099.04,"Fraud Examiners, Investigators and Analysts",0.0
-15-1211.00,Computer Systems Analysts,0.0
-15-1211.01,Health Informatics Specialists,0.0
-15-1212.00,Information Security Analysts,0.0
-15-1221.00,Computer and Information Research Scientists,0.0
-15-1231.00,Computer Network Support Specialists,0.1235
-15-1232.00,Computer User Support Specialists,0.1842
-15-1241.00,Computer Network Architects,0.0
-15-1241.01,Telecommunications Engineering Specialists,0.0732
-15-1242.00,Database Administrators,0.0
-15-1243.00,Database Architects,0.0
-15-1243.01,Data Warehousing Specialists,0.0
-15-1244.00,Network and Computer Systems Administrators,0.0366
-15-1251.00,Computer Programmers,0.0
-15-1252.00,Software Developers,0.0
-15-1253.00,Software Quality Assurance Analysts and Testers,0.0
-15-1254.00,Web Developers,0.0
-15-1255.00,Web and Digital Interface Designers,0.0
-15-1255.01,Video Game Designers,0.0
-15-1299.01,Web Administrators,0.0
-15-1299.02,Geographic Information Systems Technologists and Technicians,0.0
-15-1299.03,Document Management Specialists,0.0
-15-1299.04,Penetration Testers,0.0
-15-1299.05,Information Security Engineers,0.0
-15-1299.06,Digital Forensics Analysts,0.0875
-15-1299.07,Blockchain Engineers,0.0
-15-1299.08,Computer Systems Engineers/Architects,0.0366
-15-1299.09,Information Technology Project Managers,0.0
-15-2011.00,Actuaries,0.0
-15-2021.00,Mathematicians,0.0
-15-2031.00,Operations Research Analysts,0.0
-15-2041.00,Statisticians,0.0
-15-2041.01,Biostatisticians,0.0
-15-2051.00,Data Scientists,0.0
-15-2051.01,Business Intelligence Analysts,0.0
-15-2051.02,Clinical Data Managers,0.0
-15-2099.01,Bioinformatics Technicians,0.0
-17-1011.00,"Architects, Except Landscape and Naval",0.0
-17-1012.00,Landscape Architects,0.0
-17-1021.00,Cartographers and Photogrammetrists,0.0405
-17-1022.00,Surveyors,0.1707
-17-1022.01,Geodetic Surveyors,0.0
-17-2011.00,Aerospace Engineers,0.0
-17-2021.00,Agricultural Engineers,0.3038
-17-2031.00,Bioengineers and Biomedical Engineers,0.0976
-17-2041.00,Chemical Engineers,0.0658
-17-2051.00,Civil Engineers,0.2892
-17-2051.01,Transportation Engineers,0.0
-17-2051.02,Water/Wastewater Engineers,0.0
-17-2061.00,Computer Hardware Engineers,0.2658
-17-2071.00,Electrical Engineers,0.0
-17-2072.00,"Electronics Engineers, Except Computer",0.0976
-17-2072.01,Radio Frequency Identification Device Specialists,0.026
-17-2081.00,Environmental Engineers,0.0
-17-2111.00,"Health and Safety Engineers, Except Mining Safety Engineers and Inspectors",0.1707
-17-2111.02,Fire-Prevention and Protection Engineers,0.0
-17-2112.00,Industrial Engineers,0.0
-17-2112.01,Human Factors Engineers and Ergonomists,0.1026
-17-2112.02,Validation Engineers,0.1829
-17-2112.03,Manufacturing Engineers,0.0
-17-2121.00,Marine Engineers and Naval Architects,0.0
-17-2131.00,Materials Engineers,0.0
-17-2141.00,Mechanical Engineers,0.0
-17-2141.01,Fuel Cell Engineers,0.2469
-17-2141.02,Automotive Engineers,0.0
-17-2151.00,"Mining and Geological Engineers, Including Mining Safety Engineers",0.2353
-17-2161.00,Nuclear Engineers,0.0375
-17-2171.00,Petroleum Engineers,0.0
-17-2199.03,"Energy Engineers, Except Wind and Solar",0.0
-17-2199.05,Mechatronics Engineers,0.0519
-17-2199.06,Microsystems Engineers,0.1494
-17-2199.07,Photonics Engineers,0.381
-17-2199.08,Robotics Engineers,0.0123
-17-2199.09,Nanosystems Engineers,0.5412
-17-2199.10,Wind Energy Engineers,0.037
-17-2199.11,Solar Energy Systems Engineers,0.0
-17-3011.00,Architectural and Civil Drafters,0.1316
-17-3012.00,Electrical and Electronics Drafters,0.039
-17-3013.00,Mechanical Drafters,0.0132
-17-3021.00,Aerospace Engineering and Operations Technologists and Technicians,0.359
-17-3022.00,Civil Engineering Technologists and Technicians,0.1975
-17-3023.00,Electrical and Electronic Engineering Technologists and Technicians,0.3333
-17-3024.00,Electro-Mechanical and Mechatronics Technologists and Technicians,0.4079
-17-3024.01,Robotics Technicians,0.15
-17-3025.00,Environmental Engineering Technologists and Technicians,0.4359
-17-3026.00,Industrial Engineering Technologists and Technicians,0.2763
-17-3026.01,Nanotechnology Engineering Technologists and Technicians,1.1184
-17-3027.00,Mechanical Engineering Technologists and Technicians,0.3289
-17-3027.01,Automotive Engineering Technicians,0.321
-17-3028.00,Calibration Technologists and Technicians,0.5714
-17-3029.01,Non-Destructive Testing Specialists,0.7326
-17-3029.08,Photonics Technicians,0.8
-17-3031.00,Surveying and Mapping Technicians,0.557
-19-1011.00,Animal Scientists,0.0
-19-1012.00,Food Scientists and Technologists,0.3625
-19-1013.00,Soil and Plant Scientists,0.1408
-19-1021.00,Biochemists and Biophysicists,0.5667
-19-1022.00,Microbiologists,0.8267
-19-1023.00,Zoologists and Wildlife Biologists,0.037
-19-1029.01,Bioinformatics Scientists,0.0
-19-1029.02,Molecular and Cellular Biologists,0.3696
-19-1029.03,Geneticists,0.1868
-19-1029.04,Biologists,0.4815
-19-1031.00,Conservation Scientists,0.0759
-19-1031.02,Range Managers,0.0811
-19-1031.03,Park Naturalists,0.0541
-19-1032.00,Foresters,0.5455
-19-1041.00,Epidemiologists,0.013
-19-1042.00,"Medical Scientists, Except Epidemiologists",0.369
-19-2011.00,Astronomers,0.0
-19-2012.00,Physicists,0.1163
-19-2021.00,Atmospheric and Space Scientists,0.025
-19-2031.00,Chemists,0.9518
-19-2032.00,Materials Scientists,0.4146
-19-2041.00,"Environmental Scientists and Specialists, Including Health",0.2099
-19-2041.01,Climate Change Policy Analysts,0.0
-19-2041.02,Environmental Restoration Planners,0.0
-19-2041.03,Industrial Ecologists,0.0
-19-2042.00,"Geoscientists, Except Hydrologists and Geographers",0.1169
-19-2043.00,Hydrologists,0.141
-19-2099.01,Remote Sensing Scientists and Technologists,0.0706
-19-3011.00,Economists,0.0
-19-3011.01,Environmental Economists,0.0
-19-3022.00,Survey Researchers,0.0
-19-3032.00,Industrial-Organizational Psychologists,0.0
-19-3033.00,Clinical and Counseling Psychologists,0.0
-19-3034.00,School Psychologists,0.0
-19-3039.02,Neuropsychologists,0.0
-19-3039.03,Clinical Neuropsychologists,0.0
-19-3041.00,Sociologists,0.0
-19-3051.00,Urban and Regional Planners,0.0759
-19-3091.00,Anthropologists and Archeologists,0.1622
-19-3092.00,Geographers,0.0759
-19-3093.00,Historians,0.0
-19-3094.00,Political Scientists,0.0
-19-3099.01,Transportation Planners,0.0
-19-4012.00,Agricultural Technicians,0.974
-19-4012.01,Precision Agriculture Technicians,0.3529
-19-4013.00,Food Science Technicians,0.7051
-19-4021.00,Biological Technicians,1.0769
-19-4031.00,Chemical Technicians,0.987
-19-4042.00,"Environmental Science and Protection Technicians, Including Health",0.6053
-19-4043.00,"Geological Technicians, Except Hydrologic Technicians",0.5529
-19-4044.00,Hydrologic Technicians,0.7778
-19-4051.00,Nuclear Technicians,0.8734
-19-4051.02,Nuclear Monitoring Technicians,0.7901
-19-4061.00,Social Science Research Assistants,0.0
-19-4071.00,Forest and Conservation Technicians,0.2564
-19-4092.00,Forensic Science Technicians,0.381
-19-4099.01,Quality Control Analysts,0.4675
-19-4099.03,Remote Sensing Technicians,0.4805
-19-5011.00,Occupational Health and Safety Specialists,0.3974
-19-5012.00,Occupational Health and Safety Technicians,0.4
-21-1011.00,Substance Abuse and Behavioral Disorder Counselors,0.0
-21-1012.00,"Educational, Guidance, and Career Counselors and Advisors",0.0256
-21-1013.00,Marriage and Family Therapists,0.0
-21-1014.00,Mental Health Counselors,0.0
-21-1015.00,Rehabilitation Counselors,0.0
-21-1021.00,"Child, Family, and School Social Workers",0.0
-21-1022.00,Healthcare Social Workers,0.0
-21-1023.00,Mental Health and Substance Abuse Social Workers,0.0
-21-1091.00,Health Education Specialists,0.0
-21-1092.00,Probation Officers and Correctional Treatment Specialists,0.0488
-21-1093.00,Social and Human Service Assistants,0.0
-21-1094.00,Community Health Workers,0.2083
-21-2011.00,Clergy,0.0
-21-2021.00,"Directors, Religious Activities and Education",0.0
-23-1011.00,Lawyers,0.0
-23-1012.00,Judicial Law Clerks,0.0108
-23-1021.00,"Administrative Law Judges, Adjudicators, and Hearing Officers",0.0
-23-1022.00,"Arbitrators, Mediators, and Conciliators",0.0
-23-1023.00,"Judges, Magistrate Judges, and Magistrates",0.0
-23-2011.00,Paralegals and Legal Assistants,0.0
-23-2093.00,"Title Examiners, Abstractors, and Searchers",0.0
-25-1011.00,"Business Teachers, Postsecondary",0.0
-25-1021.00,"Computer Science Teachers, Postsecondary",0.0
-25-1022.00,"Mathematical Science Teachers, Postsecondary",0.0
-25-1031.00,"Architecture Teachers, Postsecondary",0.0
-25-1032.00,"Engineering Teachers, Postsecondary",0.0
-25-1041.00,"Agricultural Sciences Teachers, Postsecondary",0.0
-25-1042.00,"Biological Science Teachers, Postsecondary",0.0
-25-1043.00,"Forestry and Conservation Science Teachers, Postsecondary",0.0
-25-1051.00,"Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary",0.0
-25-1052.00,"Chemistry Teachers, Postsecondary",0.0303
-25-1053.00,"Environmental Science Teachers, Postsecondary",0.0
-25-1054.00,"Physics Teachers, Postsecondary",0.0
-25-1061.00,"Anthropology and Archeology Teachers, Postsecondary",0.0
-25-1062.00,"Area, Ethnic, and Cultural Studies Teachers, Postsecondary",0.0
-25-1063.00,"Economics Teachers, Postsecondary",0.0
-25-1064.00,"Geography Teachers, Postsecondary",0.0
-25-1065.00,"Political Science Teachers, Postsecondary",0.0
-25-1066.00,"Psychology Teachers, Postsecondary",0.0
-25-1067.00,"Sociology Teachers, Postsecondary",0.0
-25-1071.00,"Health Specialties Teachers, Postsecondary",0.0
-25-1072.00,"Nursing Instructors and Teachers, Postsecondary",0.0
-25-1081.00,"Education Teachers, Postsecondary",0.0
-25-1082.00,"Library Science Teachers, Postsecondary",0.0
-25-1111.00,"Criminal Justice and Law Enforcement Teachers, Postsecondary",0.0
-25-1112.00,"Law Teachers, Postsecondary",0.0
-25-1113.00,"Social Work Teachers, Postsecondary",0.0
-25-1121.00,"Art, Drama, and Music Teachers, Postsecondary",0.0116
-25-1122.00,"Communications Teachers, Postsecondary",0.0
-25-1123.00,"English Language and Literature Teachers, Postsecondary",0.0
-25-1124.00,"Foreign Language and Literature Teachers, Postsecondary",0.0
-25-1125.00,"History Teachers, Postsecondary",0.0
-25-1126.00,"Philosophy and Religion Teachers, Postsecondary",0.0
-25-1192.00,"Family and Consumer Sciences Teachers, Postsecondary",0.0
-25-1193.00,"Recreation and Fitness Studies Teachers, Postsecondary",0.0
-25-1194.00,"Career/Technical Education Teachers, Postsecondary",0.0256
-25-2011.00,"Preschool Teachers, Except Special Education",0.1781
-25-2012.00,"Kindergarten Teachers, Except Special Education",0.1348
-25-2021.00,"Elementary School Teachers, Except Special Education",0.087
-25-2022.00,"Middle School Teachers, Except Special and Career/Technical Education",0.0674
-25-2023.00,"Career/Technical Education Teachers, Middle School",0.0761
-25-2031.00,"Secondary School Teachers, Except Special and Career/Technical Education",0.0714
-25-2032.00,"Career/Technical Education Teachers, Secondary School",0.0238
-25-2051.00,"Special Education Teachers, Preschool",0.0854
-25-2055.00,"Special Education Teachers, Kindergarten",0.0562
-25-2056.00,"Special Education Teachers, Elementary School",0.023
-25-2057.00,"Special Education Teachers, Middle School",0.0556
-25-2058.00,"Special Education Teachers, Secondary School",0.0337
-25-2059.01,Adapted Physical Education Specialists,0.0128
-25-3011.00,"Adult Basic Education, Adult Secondary Education, and English as a Second Language Instructors",0.0635
-25-3021.00,Self-Enrichment Teachers,0.0702
-25-3031.00,"Substitute Teachers, Short-Term",0.1458
-25-3041.00,Tutors,0.0392
-25-4011.00,Archivists,0.0779
-25-4012.00,Curators,0.0732
-25-4013.00,Museum Technicians and Conservators,0.1351
-25-4022.00,Librarians and Media Collections Specialists,0.0526
-25-4031.00,Library Technicians,0.4706
-25-9021.00,Farm and Home Management Educators,0.08
-25-9031.00,Instructional Coordinators,0.0
-25-9042.00,"Teaching Assistants, Preschool, Elementary, Middle, and Secondary School, Except Special Education",0.2273
-25-9043.00,"Teaching Assistants, Special Education",0.1029
-25-9044.00,"Teaching Assistants, Postsecondary",0.1026
-27-1011.00,Art Directors,0.0
-27-1012.00,Craft Artists,0.6267
-27-1013.00,"Fine Artists, Including Painters, Sculptors, and Illustrators",0.6164
-27-1014.00,Special Effects Artists and Animators,0.025
-27-1021.00,Commercial and Industrial Designers,0.0366
-27-1022.00,Fashion Designers,0.0494
-27-1023.00,Floral Designers,0.3514
-27-1024.00,Graphic Designers,0.0
-27-1025.00,Interior Designers,0.0533
-27-1026.00,Merchandise Displayers and Window Trimmers,0.3151
-27-1027.00,Set and Exhibit Designers,0.0366
-27-2011.00,Actors,0.0484
-27-2012.00,Producers and Directors,0.0
-27-2012.03,Media Programming Directors,0.0
-27-2012.04,Talent Directors,0.0
-27-2012.05,Media Technical Directors/Managers,0.1299
-27-2021.00,Athletes and Sports Competitors,0.0
-27-2022.00,Coaches and Scouts,0.0
-27-2023.00,"Umpires, Referees, and Other Sports Officials",0.0571
-27-2031.00,Dancers,0.0563
-27-2032.00,Choreographers,0.0
-27-2041.00,Music Directors and Composers,0.0
-27-2042.00,Musicians and Singers,0.1852
-27-2091.00,"Disc Jockeys, Except Radio",0.1833
-27-3011.00,Broadcast Announcers and Radio Disc Jockeys,0.0
-27-3023.00,"News Analysts, Reporters, and Journalists",0.0723
-27-3031.00,Public Relations Specialists,0.0
-27-3041.00,Editors,0.0
-27-3042.00,Technical Writers,0.0
-27-3043.00,Writers and Authors,0.0
-27-3043.05,"Poets, Lyricists and Creative Writers",0.0
-27-3091.00,Interpreters and Translators,0.0
-27-3092.00,Court Reporters and Simultaneous Captioners,0.0253
-27-4011.00,Audio and Video Technicians,0.037
-27-4012.00,Broadcast Technicians,0.0854
-27-4014.00,Sound Engineering Technicians,0.2597
-27-4015.00,Lighting Technicians,0.5422
-27-4021.00,Photographers,0.2027
-27-4031.00,"Camera Operators, Television, Video, and Film",0.5309
-27-4032.00,Film and Video Editors,0.0
-29-1011.00,Chiropractors,0.0
-29-1021.00,"Dentists, General",0.0
-29-1022.00,Oral and Maxillofacial Surgeons,0.013
-29-1023.00,Orthodontists,0.04
-29-1024.00,Prosthodontists,0.0845
-29-1031.00,Dietitians and Nutritionists,0.0779
-29-1041.00,Optometrists,0.0
-29-1051.00,Pharmacists,0.3125
-29-1071.00,Physician Assistants,0.0
-29-1071.01,Anesthesiologist Assistants,0.6742
-29-1081.00,Podiatrists,0.0
-29-1122.00,Occupational Therapists,0.1039
-29-1122.01,"Low Vision Therapists, Orientation and Mobility Specialists, and Vision Rehabilitation Therapists",0.0
-29-1123.00,Physical Therapists,0.1067
-29-1124.00,Radiation Therapists,0.6456
-29-1125.00,Recreational Therapists,0.3077
-29-1126.00,Respiratory Therapists,0.1081
-29-1127.00,Speech-Language Pathologists,0.0
-29-1128.00,Exercise Physiologists,0.0417
-29-1129.01,Art Therapists,0.0556
-29-1129.02,Music Therapists,0.0
-29-1131.00,Veterinarians,0.0
-29-1141.00,Registered Nurses,0.0137
-29-1141.01,Acute Care Nurses,0.026
-29-1141.02,Advanced Practice Psychiatric Nurses,0.0
-29-1141.03,Critical Care Nurses,0.0137
-29-1141.04,Clinical Nurse Specialists,0.0
-29-1151.00,Nurse Anesthetists,0.1786
-29-1161.00,Nurse Midwives,0.0
-29-1171.00,Nurse Practitioners,0.0
-29-1181.00,Audiologists,0.0
-29-1211.00,Anesthesiologists,0.2385
-29-1212.00,Cardiologists,0.0288
-29-1213.00,Dermatologists,0.0
-29-1214.00,Emergency Medicine Physicians,0.0
-29-1215.00,Family Medicine Physicians,0.0
-29-1216.00,General Internal Medicine Physicians,0.0
-29-1217.00,Neurologists,0.0
-29-1218.00,Obstetricians and Gynecologists,0.0
-29-1221.00,"Pediatricians, General",0.0
-29-1222.00,"Physicians, Pathologists",0.0
-29-1223.00,Psychiatrists,0.0
-29-1224.00,Radiologists,0.0
-29-1229.01,Allergists and Immunologists,0.0
-29-1229.02,Hospitalists,0.0
-29-1229.03,Urologists,0.0
-29-1229.04,Physical Medicine and Rehabilitation Physicians,0.0
-29-1229.05,Preventive Medicine Physicians,0.0
-29-1229.06,Sports Medicine Physicians,0.01
-29-1241.00,"Ophthalmologists, Except Pediatric",0.0303
-29-1242.00,"Orthopedic Surgeons, Except Pediatric",0.0
-29-1243.00,Pediatric Surgeons,0.0
-29-1291.00,Acupuncturists,0.3906
-29-1292.00,Dental Hygienists,0.0635
-29-1299.01,Naturopathic Physicians,0.3099
-29-1299.02,Orthoptists,0.0541
-29-2011.00,Medical and Clinical Laboratory Technologists,0.8961
-29-2011.01,Cytogenetic Technologists,0.4231
-29-2011.02,Cytotechnologists,0.3896
-29-2011.04,Histotechnologists,1.039
-29-2012.00,Medical and Clinical Laboratory Technicians,0.8961
-29-2012.01,Histology Technicians,0.9733
-29-2031.00,Cardiovascular Technologists and Technicians,0.0395
-29-2032.00,Diagnostic Medical Sonographers,0.0256
-29-2033.00,Nuclear Medicine Technologists,0.8026
-29-2034.00,Radiologic Technologists and Technicians,0.4342
-29-2035.00,Magnetic Resonance Imaging Technologists,0.039
-29-2036.00,Medical Dosimetrists,0.026
-29-2042.00,Emergency Medical Technicians,0.3636
-29-2043.00,Paramedics,0.0741
-29-2051.00,Dietetic Technicians,0.0649
-29-2052.00,Pharmacy Technicians,0.6197
-29-2053.00,Psychiatric Technicians,0.1486
-29-2055.00,Surgical Technologists,0.1558
-29-2056.00,Veterinary Technologists and Technicians,0.2895
-29-2057.00,Ophthalmic Medical Technicians,0.9041
-29-2061.00,Licensed Practical and Licensed Vocational Nurses,0.1644
-29-2072.00,Medical Records Specialists,0.0405
-29-2081.00,"Opticians, Dispensing",0.1507
-29-2091.00,Orthotists and Prosthetists,0.0741
-29-2092.00,Hearing Aid Specialists,0.0
-29-2099.01,Neurodiagnostic Technologists,0.0526
-29-2099.05,Ophthalmic Medical Technologists,0.7105
-29-2099.08,Patient Representatives,0.0
-29-9021.00,Health Information Technologists and Medical Registrars,0.0
-29-9091.00,Athletic Trainers,0.1579
-29-9092.00,Genetic Counselors,0.0
-29-9093.00,Surgical Assistants,0.2338
-29-9099.01,Midwives,0.0455
-31-1121.00,Home Health Aides,0.3939
-31-1122.00,Personal Care Aides,0.3846
-31-1131.00,Nursing Assistants,0.2083
-31-1132.00,Orderlies,0.9211
-31-1133.00,Psychiatric Aides,0.0921
-31-2011.00,Occupational Therapy Assistants,0.0676
-31-2012.00,Occupational Therapy Aides,0.4225
-31-2021.00,Physical Therapist Assistants,0.5
-31-2022.00,Physical Therapist Aides,0.6094
-31-9011.00,Massage Therapists,0.2037
-31-9091.00,Dental Assistants,0.0972
-31-9092.00,Medical Assistants,0.3867
-31-9093.00,Medical Equipment Preparers,0.9231
-31-9094.00,Medical Transcriptionists,0.0278
-31-9095.00,Pharmacy Aides,0.6825
-31-9096.00,Veterinary Assistants and Laboratory Animal Caretakers,0.3889
-31-9097.00,Phlebotomists,1.0139
-31-9099.01,Speech-Language Pathology Assistants,0.1944
-31-9099.02,Endoscopy Technicians,0.4605
-33-1011.00,First-Line Supervisors of Correctional Officers,0.0118
-33-1012.00,First-Line Supervisors of Police and Detectives,0.0345
-33-1021.00,First-Line Supervisors of Firefighting and Prevention Workers,0.1974
-33-1091.00,First-Line Supervisors of Security Workers,0.3951
-33-2011.00,Firefighters,0.2571
-33-2021.00,Fire Inspectors and Investigators,0.0122
-33-2022.00,Forest Fire Inspectors and Prevention Specialists,0.439
-33-3011.00,Bailiffs,0.3684
-33-3012.00,Correctional Officers and Jailers,0.2111
-33-3021.00,Detectives and Criminal Investigators,0.1429
-33-3021.02,Police Identification and Records Officers,0.1294
-33-3021.06,Intelligence Analysts,0.038
-33-3031.00,Fish and Game Wardens,0.1839
-33-3041.00,Parking Enforcement Workers,1.0132
-33-3051.00,Police and Sheriff's Patrol Officers,0.1294
-33-3051.04,Customs and Border Protection Officers,0.011
-33-3052.00,Transit and Railroad Police,0.8148
-33-9011.00,Animal Control Workers,0.175
-33-9021.00,Private Detectives and Investigators,0.0244
-33-9031.00,Gambling Surveillance Officers and Gambling Investigators,0.0
-33-9032.00,Security Guards,1.025
-33-9091.00,Crossing Guards and Flaggers,0.7091
-33-9092.00,"Lifeguards, Ski Patrol, and Other Recreational Protective Service Workers",0.7458
-33-9093.00,Transportation Security Screeners,0.4079
-33-9094.00,School Bus Monitors,0.0526
-33-9099.02,Retail Loss Prevention Specialists,0.1975
-35-1011.00,Chefs and Head Cooks,0.0968
-35-1012.00,First-Line Supervisors of Food Preparation and Serving Workers,0.3529
-35-2011.00,"Cooks, Fast Food",1.2069
-35-2012.00,"Cooks, Institution and Cafeteria",0.8676
-35-2013.00,"Cooks, Private Household",0.8406
-35-2014.00,"Cooks, Restaurant",0.8933
-35-2015.00,"Cooks, Short Order",1.1385
-35-2021.00,Food Preparation Workers,1.0339
-35-3011.00,Bartenders,0.8413
-35-3023.00,Fast Food and Counter Workers,0.9
-35-3023.01,Baristas,1.037
-35-3031.00,Waiters and Waitresses,0.6182
-35-3041.00,"Food Servers, Nonrestaurant",0.9833
-35-9011.00,Dining Room and Cafeteria Attendants and Bartender Helpers,1.1455
-35-9021.00,Dishwashers,1.4915
-35-9031.00,"Hosts and Hostesses, Restaurant, Lounge, and Coffee Shop",0.9434
-37-1011.00,First-Line Supervisors of Housekeeping and Janitorial Workers,0.1084
-37-1012.00,"First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers",0.3333
-37-2011.00,"Janitors and Cleaners, Except Maids and Housekeeping Cleaners",1.0758
-37-2012.00,Maids and Housekeeping Cleaners,0.8308
-37-2021.00,Pest Control Workers,0.6786
-37-3011.00,Landscaping and Groundskeeping Workers,1.2632
-37-3012.00,"Pesticide Handlers, Sprayers, and Applicators, Vegetation",1.4462
-37-3013.00,Tree Trimmers and Pruners,0.4938
-39-1013.00,First-Line Supervisors of Gambling Services Workers,0.122
-39-1014.00,"First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services",0.1235
-39-1022.00,First-Line Supervisors of Personal Service Workers,0.1449
-39-2011.00,Animal Trainers,0.1972
-39-2021.00,Animal Caretakers,0.5915
-39-3011.00,Gambling Dealers,0.9138
-39-3012.00,Gambling and Sports Book Writers and Runners,1.3676
-39-3021.00,Motion Picture Projectionists,1.0862
-39-3031.00,"Ushers, Lobby Attendants, and Ticket Takers",0.7857
-39-3091.00,Amusement and Recreation Attendants,0.6111
-39-3092.00,Costume Attendants,0.44
-39-3093.00,"Locker Room, Coatroom, and Dressing Room Attendants",0.8983
-39-4011.00,Embalmers,0.1446
-39-4012.00,Crematory Operators,0.6301
-39-4021.00,Funeral Attendants,0.5224
-39-4031.00,"Morticians, Undertakers, and Funeral Arrangers",0.2353
-39-5011.00,Barbers,0.1389
-39-5012.00,"Hairdressers, Hairstylists, and Cosmetologists",0.3636
-39-5091.00,"Makeup Artists, Theatrical and Performance",0.0571
-39-5092.00,Manicurists and Pedicurists,0.1
-39-5093.00,Shampooers,1.8462
-39-5094.00,Skincare Specialists,0.1194
-39-6011.00,Baggage Porters and Bellhops,0.8378
-39-6012.00,Concierges,0.3182
-39-7011.00,Tour Guides and Escorts,0.6552
-39-7012.00,Travel Guides,0.7927
-39-9011.00,Childcare Workers,0.1111
-39-9011.01,Nannies,0.2353
-39-9031.00,Exercise Trainers and Group Fitness Instructors,0.05
-39-9032.00,Recreation Workers,0.0
-39-9041.00,Residential Advisors,0.1818
-41-1011.00,First-Line Supervisors of Retail Sales Workers,0.2299
-41-1012.00,First-Line Supervisors of Non-Retail Sales Workers,0.0337
-41-2011.00,Cashiers,1.0
-41-2012.00,Gambling Change Persons and Booth Cashiers,1.3676
-41-2021.00,Counter and Rental Clerks,0.1719
-41-2022.00,Parts Salespersons,0.5789
-41-2031.00,Retail Salespersons,0.7258
-41-3011.00,Advertising Sales Agents,0.0
-41-3021.00,Insurance Sales Agents,0.0361
-41-3031.00,"Securities, Commodities, and Financial Services Sales Agents",0.0
-41-3041.00,Travel Agents,0.0
-41-3091.00,"Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel",0.0256
-41-4011.00,"Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products",0.0119
-41-4011.07,Solar Sales Representatives and Assessors,0.1829
-41-4012.00,"Sales Representatives, Wholesale and Manufacturing, Except Technical and Scientific Products",0.1
-41-9011.00,Demonstrators and Product Promoters,0.8667
-41-9012.00,Models,0.0
-41-9021.00,Real Estate Brokers,0.0
-41-9022.00,Real Estate Sales Agents,0.0274
-41-9031.00,Sales Engineers,0.0
-41-9041.00,Telemarketers,0.0
-41-9091.00,"Door-to-Door Sales Workers, News and Street Vendors, and Related Workers",1.3636
-43-1011.00,First-Line Supervisors of Office and Administrative Support Workers,0.0
-43-2011.00,"Switchboard Operators, Including Answering Service",0.0571
-43-2021.00,Telephone Operators,0.1096
-43-3011.00,Bill and Account Collectors,0.0
-43-3021.00,Billing and Posting Clerks,0.0921
-43-3031.00,"Bookkeeping, Accounting, and Auditing Clerks",0.0685
-43-3041.00,Gambling Cage Workers,1.1781
-43-3051.00,Payroll and Timekeeping Clerks,0.013
-43-3061.00,Procurement Clerks,0.026
-43-3071.00,Tellers,1.1212
-43-4011.00,Brokerage Clerks,0.1579
-43-4021.00,Correspondence Clerks,0.0267
-43-4031.00,"Court, Municipal, and License Clerks",0.2105
-43-4041.00,"Credit Authorizers, Checkers, and Clerks",0.0526
-43-4051.00,Customer Service Representatives,0.0
-43-4061.00,"Eligibility Interviewers, Government Programs",0.0
-43-4071.00,File Clerks,0.6429
-43-4081.00,"Hotel, Motel, and Resort Desk Clerks",0.0746
-43-4111.00,"Interviewers, Except Eligibility and Loan",0.0
-43-4121.00,"Library Assistants, Clerical",0.8182
-43-4131.00,Loan Interviewers and Clerks,0.0
-43-4141.00,New Accounts Clerks,0.5132
-43-4151.00,Order Clerks,0.0
-43-4161.00,"Human Resources Assistants, Except Payroll and Timekeeping",0.0649
-43-4171.00,Receptionists and Information Clerks,0.2222
-43-4181.00,Reservation and Transportation Ticket Agents and Travel Clerks,0.2319
-43-5011.00,Cargo and Freight Agents,0.275
-43-5011.01,Freight Forwarders,0.0
-43-5021.00,Couriers and Messengers,1.4928
-43-5031.00,Public Safety Telecommunicators,0.0
-43-5032.00,"Dispatchers, Except Police, Fire, and Ambulance",0.026
-43-5041.00,"Meter Readers, Utilities",1.6711
-43-5051.00,Postal Service Clerks,1.0779
-43-5052.00,Postal Service Mail Carriers,1.1364
-43-5053.00,"Postal Service Mail Sorters, Processors, and Processing Machine Operators",1.1446
-43-5061.00,"Production, Planning, and Expediting Clerks",0.0
-43-5071.00,"Shipping, Receiving, and Inventory Clerks",0.6494
-43-5111.00,"Weighers, Measurers, Checkers, and Samplers, Recordkeeping",0.8933
-43-6011.00,Executive Secretaries and Executive Administrative Assistants,0.0519
-43-6012.00,Legal Secretaries and Administrative Assistants,0.25
-43-6013.00,Medical Secretaries and Administrative Assistants,0.0395
-43-6014.00,"Secretaries and Administrative Assistants, Except Legal, Medical, and Executive",0.2162
-43-9021.00,Data Entry Keyers,0.1045
-43-9022.00,Word Processors and Typists,0.32
-43-9031.00,Desktop Publishers,0.0
-43-9041.00,Insurance Claims and Policy Processing Clerks,0.0
-43-9051.00,"Mail Clerks and Mail Machine Operators, Except Postal Service",1.0135
-43-9061.00,"Office Clerks, General",0.5211
-43-9071.00,"Office Machine Operators, Except Computer",1.0263
-43-9081.00,Proofreaders and Copy Markers,0.0
-43-9111.00,Statistical Assistants,0.0641
-45-1011.00,"First-Line Supervisors of Farming, Fishing, and Forestry Workers",0.7174
-45-2011.00,Agricultural Inspectors,0.1538
-45-2021.00,Animal Breeders,0.9286
-45-2041.00,"Graders and Sorters, Agricultural Products",0.9744
-45-2091.00,Agricultural Equipment Operators,2.1277
-45-2092.00,"Farmworkers and Laborers, Crop, Nursery, and Greenhouse",1.1573
-45-2093.00,"Farmworkers, Farm, Ranch, and Aquacultural Animals",1.2872
-45-3031.00,Fishing and Hunting Workers,0.5172
-45-4011.00,Forest and Conservation Workers,1.1486
-45-4021.00,Fallers,0.4815
-45-4022.00,Logging Equipment Operators,1.0357
-45-4023.00,Log Graders and Scalers,0.95
-47-1011.00,First-Line Supervisors of Construction Trades and Extraction Workers,0.7263
-47-1011.03,Solar Energy Installation Managers,0.046
-47-2011.00,Boilermakers,0.8795
-47-2021.00,Brickmasons and Blockmasons,1.4167
-47-2022.00,Stonemasons,1.2025
-47-2031.00,Carpenters,0.6951
-47-2041.00,Carpet Installers,0.75
-47-2042.00,"Floor Layers, Except Carpet, Wood, and Hard Tiles",0.9444
-47-2043.00,Floor Sanders and Finishers,1.0
-47-2044.00,Tile and Stone Setters,0.9067
-47-2051.00,Cement Masons and Concrete Finishers,1.0286
-47-2053.00,Terrazzo Workers and Finishers,1.2468
-47-2061.00,Construction Laborers,1.0494
-47-2071.00,"Paving, Surfacing, and Tamping Equipment Operators",1.8488
-47-2072.00,Pile Driver Operators,0.0909
-47-2073.00,Operating Engineers and Other Construction Equipment Operators,1.6
-47-2081.00,Drywall and Ceiling Tile Installers,1.0811
-47-2082.00,Tapers,1.5946
-47-2111.00,Electricians,0.3289
-47-2121.00,Glaziers,0.9241
-47-2131.00,"Insulation Workers, Floor, Ceiling, and Wall",0.9296
-47-2132.00,"Insulation Workers, Mechanical",0.3625
-47-2141.00,"Painters, Construction and Maintenance",0.6714
-47-2142.00,Paperhangers,0.9589
-47-2151.00,Pipelayers,1.025
-47-2152.00,"Plumbers, Pipefitters, and Steamfitters",0.5122
-47-2152.04,Solar Thermal Installers and Technicians,0.5915
-47-2161.00,Plasterers and Stucco Masons,1.0741
-47-2171.00,Reinforcing Iron and Rebar Workers,0.9221
-47-2181.00,Roofers,0.5147
-47-2211.00,Sheet Metal Workers,0.8571
-47-2221.00,Structural Iron and Steel Workers,0.925
-47-2231.00,Solar Photovoltaic Installers,0.5316
-47-3011.00,"Helpers--Brickmasons, Blockmasons, Stonemasons, and Tile and Marble Setters",1.3077
-47-3012.00,Helpers--Carpenters,1.2821
-47-3013.00,Helpers--Electricians,0.8537
-47-3014.00,"Helpers--Painters, Paperhangers, Plasterers, and Stucco Masons",0.7838
-47-3015.00,"Helpers--Pipelayers, Plumbers, Pipefitters, and Steamfitters",0.8025
-47-3016.00,Helpers--Roofers,0.7857
-47-4011.00,Construction and Building Inspectors,0.2
-47-4011.01,Energy Auditors,0.0429
-47-4021.00,Elevator and Escalator Installers and Repairers,0.2564
-47-4031.00,Fence Erectors,1.0405
-47-4041.00,Hazardous Materials Removal Workers,0.7195
-47-4051.00,Highway Maintenance Workers,1.3765
-47-4061.00,Rail-Track Laying and Maintenance Equipment Operators,1.2055
-47-4071.00,Septic Tank Servicers and Sewer Pipe Cleaners,0.7558
-47-4091.00,Segmental Pavers,0.321
-47-4099.03,Weatherization Installers and Technicians,0.5063
-47-5011.00,"Derrick Operators, Oil and Gas",1.3118
-47-5012.00,"Rotary Drill Operators, Oil and Gas",1.3125
-47-5013.00,"Service Unit Operators, Oil and Gas",0.7453
-47-5022.00,"Excavating and Loading Machine and Dragline Operators, Surface Mining",1.6136
-47-5023.00,"Earth Drillers, Except Oil and Gas",1.1744
-47-5032.00,"Explosives Workers, Ordnance Handling Experts, and Blasters",1.1591
-47-5041.00,Continuous Mining Machine Operators,0.9518
-47-5043.00,"Roof Bolters, Mining",0.9425
-47-5044.00,"Loading and Moving Machine Operators, Underground Mining",1.0341
-47-5051.00,"Rock Splitters, Quarry",0.7222
-47-5071.00,"Roustabouts, Oil and Gas",0.7442
-47-5081.00,Helpers--Extraction Workers,0.9667
-49-1011.00,"First-Line Supervisors of Mechanics, Installers, and Repairers",0.2093
-49-2011.00,"Computer, Automated Teller, and Office Machine Repairers",0.4267
-49-2021.00,"Radio, Cellular, and Tower Equipment Installers and Repairers",0.8095
-49-2022.00,"Telecommunications Equipment Installers and Repairers, Except Line Installers",0.5488
-49-2091.00,Avionics Technicians,0.3671
-49-2092.00,"Electric Motor, Power Tool, and Related Repairers",0.7195
-49-2093.00,"Electrical and Electronics Installers and Repairers, Transportation Equipment",0.3291
-49-2094.00,"Electrical and Electronics Repairers, Commercial and Industrial Equipment",0.2346
-49-2095.00,"Electrical and Electronics Repairers, Powerhouse, Substation, and Relay",0.3951
-49-2096.00,"Electronic Equipment Installers and Repairers, Motor Vehicles",0.1757
-49-2097.00,Audiovisual Equipment Installers and Repairers,0.1184
-49-2098.00,Security and Fire Alarm Systems Installers,0.5443
-49-3011.00,Aircraft Mechanics and Service Technicians,0.225
-49-3021.00,Automotive Body and Related Repairers,0.4815
-49-3022.00,Automotive Glass Installers and Repairers,0.625
-49-3023.00,Automotive Service Technicians and Mechanics,0.2405
-49-3031.00,Bus and Truck Mechanics and Diesel Engine Specialists,0.125
-49-3041.00,Farm Equipment Mechanics and Service Technicians,0.2209
-49-3042.00,"Mobile Heavy Equipment Mechanics, Except Engines",0.2024
-49-3043.00,Rail Car Repairers,0.1667
-49-3051.00,Motorboat Mechanics and Service Technicians,0.1795
-49-3052.00,Motorcycle Mechanics,0.2192
-49-3053.00,Outdoor Power Equipment and Other Small Engine Mechanics,0.2727
-49-3091.00,Bicycle Repairers,0.2162
-49-3092.00,Recreational Vehicle Service Technicians,0.1111
-49-3093.00,Tire Repairers and Changers,0.9718
-49-9011.00,Mechanical Door Repairers,0.4861
-49-9012.00,"Control and Valve Installers and Repairers, Except Mechanical Door",0.7333
-49-9021.00,"Heating, Air Conditioning, and Refrigeration Mechanics and Installers",0.4625
-49-9031.00,Home Appliance Repairers,0.4384
-49-9041.00,Industrial Machinery Mechanics,0.2716
-49-9043.00,"Maintenance Workers, Machinery",0.7051
-49-9044.00,Millwrights,0.6588
-49-9045.00,"Refractory Materials Repairers, Except Brickmasons",0.8493
-49-9051.00,Electrical Power-Line Installers and Repairers,0.9205
-49-9052.00,Telecommunications Line Installers and Repairers,0.6988
-49-9061.00,Camera and Photographic Equipment Repairers,0.2973
-49-9062.00,Medical Equipment Repairers,0.2436
-49-9063.00,Musical Instrument Repairers and Tuners,0.1343
-49-9064.00,Watch and Clock Repairers,0.3816
-49-9071.00,"Maintenance and Repair Workers, General",0.3494
-49-9081.00,Wind Turbine Service Technicians,0.4198
-49-9091.00,"Coin, Vending, and Amusement Machine Servicers and Repairers",0.4444
-49-9092.00,Commercial Divers,0.663
-49-9094.00,Locksmiths and Safe Repairers,0.4928
-49-9095.00,Manufactured Building and Mobile Home Installers,0.1875
-49-9096.00,Riggers,0.575
-49-9097.00,Signal and Track Switch Repairers,0.7386
-49-9098.00,"Helpers--Installation, Maintenance, and Repair Workers",1.0123
-49-9099.01,Geothermal Technicians,0.5067
-51-1011.00,First-Line Supervisors of Production and Operating Workers,0.1011
-51-2011.00,"Aircraft Structure, Surfaces, Rigging, and Systems Assemblers",0.7805
-51-2021.00,"Coil Winders, Tapers, and Finishers",0.8875
-51-2022.00,Electrical and Electronic Equipment Assemblers,0.8875
-51-2023.00,Electromechanical Equipment Assemblers,0.8875
-51-2031.00,Engine and Other Machine Assemblers,0.8395
-51-2041.00,Structural Metal Fabricators and Fitters,0.9268
-51-2051.00,Fiberglass Laminators and Fabricators,0.8077
-51-2061.00,Timing Device Assemblers and Adjusters,0.7808
-51-2092.00,Team Assemblers,0.8718
-51-3011.00,Bakers,0.8649
-51-3021.00,Butchers and Meat Cutters,0.92
-51-3022.00,"Meat, Poultry, and Fish Cutters and Trimmers",0.8933
-51-3023.00,Slaughterers and Meat Packers,0.8481
-51-3091.00,"Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders",1.3974
-51-3092.00,Food Batchmakers,1.1266
-51-3093.00,Food Cooking Machine Operators and Tenders,1.1781
-51-4021.00,"Extruding and Drawing Machine Setters, Operators, and Tenders, Metal and Plastic",0.963
-51-4022.00,"Forging Machine Setters, Operators, and Tenders, Metal and Plastic",0.9512
-51-4023.00,"Rolling Machine Setters, Operators, and Tenders, Metal and Plastic",0.9634
-51-4031.00,"Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic",1.0988
-51-4032.00,"Drilling and Boring Machine Tool Setters, Operators, and Tenders, Metal and Plastic",0.9351
-51-4033.00,"Grinding, Lapping, Polishing, and Buffing Machine Tool Setters, Operators, and Tenders, Metal and Plastic",0.875
-51-4034.00,"Lathe and Turning Machine Tool Setters, Operators, and Tenders, Metal and Plastic",1.0854
-51-4035.00,"Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic",1.1875
-51-4041.00,Machinists,0.8293
-51-4051.00,Metal-Refining Furnace Operators and Tenders,1.369
-51-4052.00,"Pourers and Casters, Metal",1.3125
-51-4061.00,"Model Makers, Metal and Plastic",0.7821
-51-4062.00,"Patternmakers, Metal and Plastic",0.7531
-51-4071.00,Foundry Mold and Coremakers,1.0
-51-4072.00,"Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic",1.1625
-51-4081.00,"Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic",1.0
-51-4111.00,Tool and Die Makers,0.5897
-51-4121.00,"Welders, Cutters, Solderers, and Brazers",0.963
-51-4122.00,"Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders",0.9753
-51-4191.00,"Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic",0.8375
-51-4192.00,"Layout Workers, Metal and Plastic",0.7561
-51-4193.00,"Plating Machine Setters, Operators, and Tenders, Metal and Plastic",0.9518
-51-4194.00,"Tool Grinders, Filers, and Sharpeners",1.038
-51-5111.00,Prepress Technicians and Workers,0.4675
-51-5112.00,Printing Press Operators,0.963
-51-5113.00,Print Binding and Finishing Workers,1.05
-51-6011.00,Laundry and Dry-Cleaning Workers,0.8657
-51-6021.00,"Pressers, Textile, Garment, and Related Materials",0.9041
-51-6031.00,Sewing Machine Operators,0.8784
-51-6041.00,Shoe and Leather Workers and Repairers,0.3026
-51-6042.00,Shoe Machine Operators and Tenders,1.0519
-51-6051.00,"Sewers, Hand",0.96
-51-6052.00,"Tailors, Dressmakers, and Custom Sewers",0.2113
-51-6061.00,Textile Bleaching and Dyeing Machine Operators and Tenders,0.9136
-51-6062.00,"Textile Cutting Machine Setters, Operators, and Tenders",1.0909
-51-6063.00,"Textile Knitting and Weaving Machine Setters, Operators, and Tenders",1.1765
-51-6064.00,"Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders",1.4024
-51-6091.00,"Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers",1.15
-51-6092.00,Fabric and Apparel Patternmakers,0.1818
-51-6093.00,Upholsterers,0.1558
-51-7011.00,Cabinetmakers and Bench Carpenters,0.85
-51-7021.00,Furniture Finishers,0.6
-51-7031.00,"Model Makers, Wood",0.9737
-51-7032.00,"Patternmakers, Wood",0.8228
-51-7041.00,"Sawing Machine Setters, Operators, and Tenders, Wood",0.9398
-51-7042.00,"Woodworking Machine Setters, Operators, and Tenders, Except Sawing",0.9878
-51-8011.00,Nuclear Power Reactor Operators,0.2564
-51-8012.00,Power Distributors and Dispatchers,0.0494
-51-8013.00,Power Plant Operators,0.9048
-51-8013.03,Biomass Plant Technicians,1.3418
-51-8013.04,Hydroelectric Plant Technicians,1.0506
-51-8021.00,Stationary Engineers and Boiler Operators,1.1375
-51-8031.00,Water and Wastewater Treatment Plant and System Operators,0.963
-51-8091.00,Chemical Plant and System Operators,0.4368
-51-8092.00,Gas Plant Operators,1.2439
-51-8093.00,"Petroleum Pump System Operators, Refinery Operators, and Gaugers",0.9176
-51-8099.01,Biofuels Processing Technicians,1.2375
-51-9011.00,Chemical Equipment Operators and Tenders,0.9419
-51-9012.00,"Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders",0.9375
-51-9021.00,"Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders",1.3571
-51-9022.00,"Grinding and Polishing Workers, Hand",1.0125
-51-9023.00,"Mixing and Blending Machine Setters, Operators, and Tenders",1.0732
-51-9031.00,"Cutters and Trimmers, Hand",1.0385
-51-9032.00,"Cutting and Slicing Machine Setters, Operators, and Tenders",0.9367
-51-9041.00,"Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders",1.3537
-51-9051.00,"Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders",0.7143
-51-9061.00,"Inspectors, Testers, Sorters, Samplers, and Weighers",0.7468
-51-9071.00,Jewelers and Precious Stone and Metal Workers,0.3243
-51-9071.06,Gem and Diamond Workers,0.8889
-51-9081.00,Dental Laboratory Technicians,0.7808
-51-9082.00,Medical Appliance Technicians,0.7403
-51-9083.00,Ophthalmic Laboratory Technicians,0.7917
-51-9111.00,Packaging and Filling Machine Operators and Tenders,0.9872
-51-9123.00,"Painting, Coating, and Decorating Workers",0.8421
-51-9124.00,"Coating, Painting, and Spraying Machine Setters, Operators, and Tenders",1.025
-51-9141.00,Semiconductor Processing Technicians,1.3457
-51-9151.00,Photographic Process Workers and Processing Machine Operators,0.9429
-51-9161.00,Computer Numerically Controlled Tool Operators,1.0
-51-9162.00,Computer Numerically Controlled Tool Programmers,0.0241
-51-9191.00,Adhesive Bonding Machine Operators and Tenders,0.9744
-51-9192.00,"Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders",1.2892
-51-9193.00,Cooling and Freezing Equipment Operators and Tenders,1.2346
-51-9194.00,Etchers and Engravers,0.8676
-51-9195.00,"Molders, Shapers, and Casters, Except Metal and Plastic",0.9114
-51-9195.03,"Stone Cutters and Carvers, Manufacturing",0.9467
-51-9195.04,"Glass Blowers, Molders, Benders, and Finishers",0.8243
-51-9195.05,"Potters, Manufacturing",0.925
-51-9196.00,"Paper Goods Machine Setters, Operators, and Tenders",0.9487
-51-9197.00,Tire Builders,1.0
-51-9198.00,Helpers--Production Workers,1.2338
-53-1041.00,Aircraft Cargo Handling Supervisors,0.1067
-53-1042.00,"First-Line Supervisors of Helpers, Laborers, and Material Movers, Hand",0.5165
-53-1042.01,Recycling Coordinators,0.1875
-53-1043.00,First-Line Supervisors of Material-Moving Machine and Vehicle Operators,0.2667
-53-1044.00,First-Line Supervisors of Passenger Attendants,0.0
-53-2011.00,"Airline Pilots, Copilots, and Flight Engineers",0.5192
-53-2012.00,Commercial Pilots,0.561
-53-2021.00,Air Traffic Controllers,0.0
-53-2022.00,Airfield Operations Specialists,0.1687
-53-2031.00,Flight Attendants,0.381
-53-3011.00,"Ambulance Drivers and Attendants, Except Emergency Medical Technicians",1.0625
-53-3031.00,Driver/Sales Workers,1.7463
-53-3032.00,Heavy and Tractor-Trailer Truck Drivers,1.5098
-53-3033.00,Light Truck Drivers,2.0952
-53-3051.00,"Bus Drivers, School",1.1429
-53-3052.00,"Bus Drivers, Transit and Intercity",1.5375
-53-3053.00,Shuttle Drivers and Chauffeurs,1.9737
-53-3054.00,Taxi Drivers,2.2235
-53-4011.00,Locomotive Engineers,0.8462
-53-4013.00,"Rail Yard Engineers, Dinkey Operators, and Hostlers",1.093
-53-4022.00,"Railroad Brake, Signal, and Switch Operators and Locomotive Firers",0.6044
-53-4031.00,Railroad Conductors and Yardmasters,0.2118
-53-4041.00,Subway and Streetcar Operators,1.4177
-53-5011.00,Sailors and Marine Oilers,0.8286
-53-5021.00,"Captains, Mates, and Pilots of Water Vessels",0.8673
-53-5022.00,Motorboat Operators,1.4933
-53-5031.00,Ship Engineers,0.3231
-53-6011.00,Bridge and Lock Tenders,1.0769
-53-6021.00,Parking Attendants,1.0303
-53-6031.00,Automotive and Watercraft Service Attendants,1.5735
-53-6032.00,Aircraft Service Attendants,0.7922
-53-6041.00,Traffic Technicians,0.3514
-53-6051.00,Transportation Inspectors,0.4304
-53-6051.01,Aviation Inspectors,0.2716
-53-6051.07,"Transportation Vehicle, Equipment and Systems Inspectors, Except Aviation",0.3099
-53-6061.00,Passenger Attendants,0.1642
-53-7011.00,Conveyor Operators and Tenders,1.3086
-53-7021.00,Crane and Tower Operators,0.9167
-53-7031.00,Dredge Operators,1.6854
-53-7041.00,Hoist and Winch Operators,1.5432
-53-7051.00,Industrial Truck and Tractor Operators,1.9615
-53-7061.00,Cleaners of Vehicles and Equipment,1.0
-53-7062.00,"Laborers and Freight, Stock, and Material Movers, Hand",1.4605
-53-7062.04,Recycling and Reclamation Workers,1.6795
-53-7063.00,Machine Feeders and Offbearers,1.3896
-53-7064.00,"Packers and Packagers, Hand",1.4167
-53-7065.00,Stockers and Order Fillers,1.0145
-53-7071.00,Gas Compressor and Gas Pumping Station Operators,0.5783
-53-7072.00,"Pump Operators, Except Wellhead Pumpers",1.2118
-53-7073.00,Wellhead Pumpers,1.0349
-53-7081.00,Refuse and Recyclable Material Collectors,1.7976
-53-7121.00,"Tank Car, Truck, and Ship Loaders",1.1125

robot_exposure/robot_exposure_tasks.csv

@@ -1,3 +0,0 @@
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