README.md

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license: apache-2.0
task_categories:
- text-generation
language:
- en
---
# Dataset Card for Dataset gender_congress_117-118

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This dataset consists of definitions for gender and gender-related terms from congressional bills proposed between January 2021 and November 2023 (US Congress Sessions 117 and 118). 
It focuses on bills that feature the term "gender" prominently in the bill title, bill summary, or in the bill text. 

### Dataset Description

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- **Curated by:** Filipa Calado
- **Language(s) (NLP):** English
- **License:** Apache 2.0

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## Uses

This dataset is intended for studying bias and discrimination associated with gender and related terms. 

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### Direct Use

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### Out-of-Scope Use

As the dataset was created to study bias and discrimination in language, it is not appropriate for production or public-facing use, especially without disclosing the intention behind the dataset's curation. 
Using the dataset in ways that do not fully disclose its curation rationale can harm groups that are already marginalized. 


## Dataset Structure

The dataset contains one field, `train`, which consists of a list of definitions for gender and related terms.

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### Curation Rationale

With the anti-trans attitudes proliferating across the United States, this dataset was created to give researchers a chance to study how gender is being defined in federal legislative contexts.

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### Source Data

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#### Data Collection and Processing

The bills were originally downloaded via the [congress.gov](https://www.congress.gov) website, then processed to extract definitions of gender and related terms.

Definitions were culled from the bills by searching for terms such as:
- gender
- biological sex
- transgender
- non-binary
- queer
- lgbtqia+

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#### Who are the source data producers?
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## Bias, Risks, and Limitations

This dataset contains views of sex, gender, and sexuality that are non-affirming and harmful. 
Usage of this dataset without appropriate context (i.e., using it to share or train a model without disclosing its source and rationale) can exacerbate bias and discrimination toward marginalized groups, especially with regard to gender and gender norms.


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## Glossary [optional]

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## Dataset Card Authors

Filipa Calado

## Dataset Card Contact

gofilipa at gmail dot com