Gender, social protection systems and street‐level bureaucrats
Bibliographic record
Abstract
Abstract Street‐level bureaucrats are the “human face” of social protection delivery systems around the world. To date, most social protection literature approaches questions of gender with respect to policy and programme design and expected and unexpected outcomes. Mounting interest in gender‐responsive and rights‐based social protection systems, however, additionally begs a focus on the gendered individuals who mediate the relationship between citizens and these systems, representing the State as duty bearer of realizing the right to social protection. Much of the existing work on street‐level bureaucrats (SLBs) focuses on their use of discretion in frontline work and how this shapes beneficiary experiences. This article adapts and extends Durose and Lowndes' (2024) framework for understanding gender and SLB discretion: 1) as shaped by the gendered laws, policies and guidance of institutions where SLBs work, 2) as reflective of SLBs as gendered actors, and 3) as having gendered effects on policy beneficiaries. While their framework was developed in a high‐income context and to understand a different sector (policing), these three analytical propositions hold for SLBs in social protection systems. Yet, we suggest that understanding the role of SLBs in social protection systems requires two additional considerations from a human rights perspective: 4) discretion as shaped by the gendered social, political and economic contexts in which SLBs operate and social protection systems exist, and 5) moving beyond discretion, SLBs as rights‐holders themselves, of the right to social security and the right to decent work. The article develops this framework in conversation with scholarship on social protection systems in the broad range of contexts in which they operate. In doing so, the article offers an analytical contribution to the emerging literature on gender‐responsive social protection systems from a “frontline delivery” and human rights perspective, including their relation to Sustainable Development Goals 5 – gender equality – and 1.3 – social protection systems for all.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".