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---
language:
- en
configs:
- config_name: words
data_files:
- split: words
path: words.parquet
- config_name: associations
data_files:
- split: associations_weat
path: associations_weat.parquet
- config_name: associations_wefat
data_files:
- split: associations_wefat
path: associations_wefat.parquet
---
# Usage
When downloading, specify which files you want to download and set the split to `train` (required by `datasets`).
```python
from datasets import load_dataset
words = load_dataset("fairnlp/weat", data_files=["words.parquet"], split="train")
associations = load_dataset("fairnlp/weat", data_files=["associations_weat.parquet"], split="train")
```
# Dataset Card for Word Embedding Association Test (WEAT)
This dataset contains the source words of the original Word Embedding Association Test (WEAT) as
described [by Caliskan et. al. (2016)](https://arxiv.org/abs/1608.07187).
## Dataset Details
The dataset contains word lists and attribute lists used to compute several WEAT scores for different embedding
associations. For details on the methodology, please refer to the original paper. This dataset is contributed to Hugging
Face as part of the WEAT implementation in the [FairNLP `fairscore` library](https://github.com/FairNLP/fairscore/).
### Dataset Sources
- **Paper [optional]:** lcs.bath.ac.uk/~jjb/ftp/CaliskanSemantics-Arxiv.pdf
**BibTeX:**
```bibtex
@article{DBLP:journals/corr/IslamBN16,
author = {Aylin Caliskan Islam and
Joanna J. Bryson and
Arvind Narayanan},
title = {Semantics derived automatically from language corpora necessarily
contain human biases},
journal = {CoRR},
volume = {abs/1608.07187},
year = {2016},
url = {http://arxiv.org/abs/1608.07187},
eprinttype = {arXiv},
eprint = {1608.07187},
timestamp = {Sat, 23 Jan 2021 01:20:12 +0100},
biburl = {https://dblp.org/rec/journals/corr/IslamBN16.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
```
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