| --- |
| task_categories: |
| - text-classification |
| language: |
| - en |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: dev |
| path: data/dev-* |
| - split: test |
| path: data/test-* |
| - split: validation |
| path: data/validation-* |
| dataset_info: |
| features: |
| - name: text |
| dtype: string |
| - name: label |
| dtype: string |
| - name: label_id |
| dtype: int64 |
| - name: gender |
| dtype: string |
| - name: group_id |
| dtype: int64 |
| - name: author_id |
| dtype: string |
| - name: source_id |
| dtype: string |
| - name: job |
| dtype: string |
| - name: age |
| dtype: int64 |
| - name: age_band |
| dtype: string |
| - name: sign |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 42000916 |
| num_examples: 25956 |
| - name: dev |
| num_bytes: 5995268 |
| num_examples: 3755 |
| - name: test |
| num_bytes: 11989095 |
| num_examples: 7425 |
| - name: validation |
| num_bytes: 5995268 |
| num_examples: 3755 |
| download_size: 39778969 |
| dataset_size: 65980547 |
| --- |
| |
| # BlogTopic |
|
|
| Prepared for gender-fairness (TPR-gap) evaluation of fine-tuned language models. |
|
|
| ## Schema |
|
|
| | column | type | meaning | |
| |---|---|---| |
| | `text` | str | input text | |
| | `label` | str | task class name (Y), used as the generation target in prompted fine-tuning | |
| | `label_id` | int | contiguous class id (Y) | |
| | `gender` | str | protected attribute (Z), `female` or `male` | |
| | `group_id` | int | 0 = female, 1 = male | |
|
|
| Splits: `train`, `dev` (aliased as `validation`), `test`. |
|
|
| ## Key statistics |
|
|
| - Examples: 37,136 |
| - Classes: 26 |
| - Test P(female|Y) range: 0.186 - 0.792 |
| - Test Cramer's V (Y vs Z): 0.309 |
| - Smallest test Y x Z cell: 21 |
|
|
| Full per-class Y x Z tables are in `dataset_stats.json`. |
|
|
| ## Provenance |
|
|
| - **raw_path**: /projects/u6cg/sshao/code/peft/rep_under_control/data/raw/blog/data/blogs.zip |
| - **files_seen**: 19320 |
| - **files_skipped_bad_filename**: 0 |
| - **bloggers_skipped_unknown_industry**: 6827 |
| - **unit**: post |
| - **raw_industry_counts**: {'indunk': 6827, 'student': 5120, 'education': 980, 'technology': 943, 'arts': 721, 'communications-media': 479, 'internet': 397, 'non-profit': 372, 'engineering': 312, 'government': 236, 'law': 197, 'consulting': 191, 'science': 184, 'marketing': 180, 'businessservices': 163, 'publishing': 150, 'advertising': 145, 'religion': 139, 'telecommunications': 119, 'military': 116, 'banking': 112, 'accounting': 105, 'fashion': 98, 'humanresources': 94, 'tourism': 94, 'transportation': 91, 'sports-recreation': 90, 'manufacturing': 87, 'architecture': 69, 'chemicals': 62, 'biotech': 57, 'lawenforcement-security': 57, 'realestate': 55, 'museums-libraries': 55, 'construction': 55, 'automotive': 54, 'agriculture': 36, 'investmentbanking': 33, 'environment': 28, 'maritime': 17} |
| - **cleaning**: {'input_rows': 76872, 'dropped_unusable_gender': 0, 'dropped_too_short': 6736, 'dropped_duplicate_text': 1713, 'output_rows': 68423} |
| - **label_field**: industry |
| - **carried_metadata**: ['job', 'age', 'age_band', 'sign'] |
| - **citation**: Schler, Koppel, Argamon, Pennebaker (2006). Effects of Age and Gender on Blogging. AAAI Spring Symposium. |
| - **license**: Non-commercial research use only (per the corpus authors). |
| - **gender_source**: self-reported by the blogger at registration |
| |
| Gender is a binary proxy attribute used only to measure disparate model performance. It is not an endorsement of a binary model of gender, and for some sources it is inferred rather than self-reported (see provenance above). |
