A Commentary on “Gender Bias in Parental Attitude: An Experimental Approach” by Begum, Grossman, and Islam (2018)
Bibliographic record
Abstract
Begum et al. (2018) examined gender bias in parental attitudes using an experimental approach in rural Bangladesh. Households were reported as randomly assigned to treatment conditions in a lab-in-the-field allocation task. We show that the group assignment was inherited from Islam (2019), a previous, nonrandomized experiment conducted in the same region. The lack of randomization contradicts the design descriptions provided by the authors in Begum et al. (2018) and elsewhere and raises concerns about the validity of comparisons across treatment groups. This also points to serious shortcomings in the reporting and transparency of the study design-issues that mirror those that led to the retraction of Islam (2019) from the European Economic Review.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.058 | 0.275 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.012 | 0.006 |
| Research integrity | 0.065 | 0.082 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".