Social protection systems and gender: A review of the evidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The negative impacts of the COVID-19 pandemic have motivated an unprecedented level of global advocacy for gender-responsive and gender-transformative social protection systems that buffer individuals from shocks and vulnerabilities. This turn to a systems approach reflects growing recognition that the presence of one or two social protection programmes targeting women does not guarantee that they are protected throughout the course of their lives and over a wide range of contingencies. Relative to the high levels of interest, however, very little empirical evidence exists about what a gender-responsive or transformative social protection system entails in practice. This article departs from existing literature that focuses on the design and impact of discreet social protection instruments, to present a ‘state of the evidence’ on gender and social protection systems. Drawing on the results of a phased scoping review of academic and policy literature spanning various fields, the article charts the defining features of the existing evidence base, summarizes what is known and identifies pathways for future research. In addition to scholarly analysis, the article offers a comprehensive view of the evidence for policymakers, practitioners, movement leaders and funders working on policy problems from a gender perspective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it