Construct Validity Review: Measuring What Matters from NeurIPS 2025

A NeurIPS 2025 Datasets and Benchmarks Track review paper titled 'Measuring What Matters' provides results on construct validity. The dataset was authored by 'ambean' and last updated on November 23, 2025. It likely contains findings and analyses from a systematic review of measurement practices in machine learning.

Use Cases

• Analyzing trends in construct validity assessment based on the review's findings
• Benchmarking new evaluation metrics against reviewed standards
• Informing the design of new datasets to improve measurement quality based on the paper's conclusions

Strengths

• Directly associated with a peer-reviewed NeurIPS 2025 conference paper
• Last update timestamp is precisely recorded as 2025-11-23 16:31:39

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download
• Column-level documentation is absent; field semantics must be inferred after download
• Row count and file size are unknown, which may limit suitability assessment

Provenance

Source

huggingface

Collection Method

Results from the review paper 'Measuring What Matters'

Freshness

Last updated 2025-11-23 16:31:39; freshness should be verified