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FMAT

The Fill-Mask Association Test

The Fill-Mask Association Test ('FMAT') <doi:10.1037/pspa0000396> is an integrative, probability-based social computing method using Masked Language Models to measure conceptual associations (e.g., attitudes, biases, stereotypes, social norms, cultural values) as propositional semantic representations in natural language. Supported language models include 'BERT' <doi:10.48550/arXiv.1810.04805> and its variants available at 'Hugging Face' <https://huggingface.co/models?pipeline_tag=fill-mask>. Methodological references and installation guidance are provided at <https://psychbruce.github.io/FMAT/>.

Versions across snapshots

VersionRepositoryFileSize
2026.1 rolling source/ R- FMAT_2026.1.tar.gz 33.6 KiB
2026.1 latest source/ R- FMAT_2026.1.tar.gz 33.6 KiB
2026.1 2026-04-23 source/ R- FMAT_2026.1.tar.gz 33.6 KiB
2026.1 2026-04-09 windows/windows R-4.5 FMAT_2026.1.zip 116.0 KiB

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