Gender, professions and public policy: new directions
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
Purpose This article aims to provide an overview on key trends in public sector policy and professional development and how they intersect with gender and diversity. It seeks to explore new configurations in the relationship between gender and the professions and to develop a matrix for the collection of articles presented in this volume. Design/methodology/approach The authors link social policy and governance approaches to the study of professions, using the health professions and academics as case studies. Material from a number of studies carried out by the authors together with published secondary sources provide the basis of our analysis; this is followed by an introduction of the scope and structure of this thematic issue. Findings The findings underline the significance of public policy as key to better understand gender and diversity in professional groups. The outline of major trends in public sector professions brings into focus both the persistence of gender inequality and the emergence of new lines of gendered divisions in the professions. Practical implications The research presented here highlights a need for new models of public sector management and professional development that are more sensitive to equality and diversity. Originality/value This article focuses on the “making” of inequality at the interface of public policy and professional action. It introduces a context sensitive approach that moves beyond equal opportunity policies and managerial accounts and highlights new directions in research and policy.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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