The Invisible Hand that Rocks the Cradle: On the Limits of Time Use Surveys
Bibliographic record
Abstract
ABSTRACT Almost every intervention in the field of international agricultural development — from microcredit finance to fertilizer subsidies to trade policy — has come to recognize gender, and relationships within households, as important. Yet most interventions continue to treat the household as a ‘black box’, with changes within the household measured by the effects on income, anthropometry, health, or other secondary metrics within bargaining models. In this context, there has been increasing interest in time use studies as a way to peer inside this black box. This article offers a review of methods and identifies some of the difficulties facing time use studies in capturing intrahousehold dynamics, and presents the results of a two‐season simultaneous activity time use study in Malawi which aimed to address these difficulties. The results suggest significant limitations to time use surveys. The kinds of reproductive labour that often interest researchers may be invisible to the women responding to time use surveys, with the result that care work is dramatically under‐reported. The authors discuss the implications of the divergence between researchers’ concerns and the women's reports of their lives for time use surveys, and for feminist development research methods more broadly.
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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 | 0.458 | 0.640 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.013 | 0.028 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".