“Try to Balance the Baseline”: A comment on “Parent–teacher meetings and student outcomes: Evidence from a developing country” by Islam (2019)
Bibliographic record
Abstract
Islam (2019) reports results from a cluster randomized field experiment in Bangladesh that examines the effects of parent–teacher meetings on student test scores in primary schools. The reported findings suggest strong positive effects across multiple subjects. In this report, we demonstrate that the school-level randomization cannot have been conducted as the author claims. Specifically, we show that the nine included Bangladeshi unions all have a share of either 0% or 100% treated or control schools. Additionally, we uncover irregularities in baseline scores, which for the same students and subjects vary systematically across the author’s data files in ways that are unique to either the treatment or control group. We also discovered data on two unreported outcomes and data collected from the year before the study began. Results using these data cast further doubt on the validity of the original study. Moreover, in a survey asking parents to evaluate the parent–teacher meetings, we find that parents in the control schools were more positive about this intervention than those in the treated schools. We also find undisclosed connections to two additional RCTs.
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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 | 0.050 | 0.176 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.048 | 0.064 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".