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@@ -22,13 +22,33 @@ FerTime is a diachronic corpus spanning fertility-related documents from 1770 to
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  <!-- Provide a longer summary of what this dataset is. -->
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  FerTime was constructed by aggregating and filtering nine openly available corpora spanning newspaper archives and biomedical/clinical literature published between 1770 and the present day. The goal of the dataset is to support diachronic and cross-domain analysis of how fertility, infertility, and related reproductive-health concepts have been discussed in both lay/journalistic and clinical/scientific discourse over more than two centuries.
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- Source documents were drawn from eight aggregated datasets (American Stories, US-PD-Newspapers, PubMed, HMD Newspapers, Elsevier Open Access, CNN/DailyMail, BMJ, and MOH Reports — "London's Pulse") and filtered using a curated, regular-expression-expanded keyword list covering clinical terminology, lay vocabulary, and archaic/literary expressions related to fertility. Filtering retained approximately 2.79% of the original aggregated corpus.
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  - **Curated by:** [Agnese Lombardi — NepLab, IUSS Pavia]
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  - **Language(s) (NLP):** English (en)
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  - **License: cc-by-nc-4.0
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- ### Dataset Sources [optional]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  | Source | Link |
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  |---|---|
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  | American Stories | https://huggingface.co/datasets/dell-research-harvard/AmericanStories |
 
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  <!-- Provide a longer summary of what this dataset is. -->
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  FerTime was constructed by aggregating and filtering nine openly available corpora spanning newspaper archives and biomedical/clinical literature published between 1770 and the present day. The goal of the dataset is to support diachronic and cross-domain analysis of how fertility, infertility, and related reproductive-health concepts have been discussed in both lay/journalistic and clinical/scientific discourse over more than two centuries.
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  - **Curated by:** [Agnese Lombardi — NepLab, IUSS Pavia]
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  - **Language(s) (NLP):** English (en)
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  - **License: cc-by-nc-4.0
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+ #### Data Collection and Processing
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+ <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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+ Documents were aggregated from nine source datasets (listed above) and filtered using a predefined, regex-expanded keyword list covering clinical terminology, lay/journalistic vocabulary, and archaic or literary expressions related to fertility, drawing on prior terminological work in reproductive medicine. The keyword list includes: *fertility, infertility, sterility, barrenness, fecundity, conception, pregnancy, childlessness, miscarriage, womb, uterus, ovary, ovulation, semen, sperm, birth rate, procreation, reproduction, natality, childbearing, progeny, offspring, heir, fallow, unfruitful, bear children, blessed with children, denied children, curse of barrenness*. Regular expressions captured inflectional and derivational variants of these terms. The overall retention rate after filtering was approximately 2.79% of the original aggregated corpus.
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+ **Table: Corpus size before and after keyword-based filtering**
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+ | Source | Pre-filtering | Post-filtering | % Retained |
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+ |---|---:|---:|---:|
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+ | American Stories | 272,559,714 | 3,563,938 | 1.31% |
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+ | US-PD-Newspapers | 21,226,700 | 4,259,736 | 20.07% |
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+ | PubMed | 13,803,820 | 529,185 | 3.83% |
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+ | HMD Newspapers | 1,494,729 | 149,855 | 10.03% |
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+ | Elsevier Open Access | 432,266 | 114,262 | 26.43% |
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+ | CNN/DailyMail | 287,107 | 16,650 | 5.80% |
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+ | BMJ (Internet Archive) | 7,380 | 6,424 | 87.05% |
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+ | MOH Reports (Wellcome) | 694 | 583 | 84.01% |
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+ | **Total** | **309,812,410** | **8,640,633** | **2.79%** |
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+ Retention rates vary substantially by source, reflecting differences in genre and topical focus: clinical and specialized archives with an inherent focus on health/reproduction (BMJ, MOH Reports, Elsevier Open Access) show much higher retention than general-purpose newspaper and news corpora (American Stories, CNN/DailyMail), where fertility-related content is comparatively rare relative to overall volume.
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+ ### Dataset Sources
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  | Source | Link |
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  |---|---|
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  | American Stories | https://huggingface.co/datasets/dell-research-harvard/AmericanStories |