Bibliographic record
Abstract
Articles: Nannies, Nurses and Nuns: Broadening the Scope of Global Care Chain Analysis - N.Yeates Caring Across Borders: The Case of Women Health Workers from Kerala in the Middle East - U.Devi Entrenching Gender Discrimination? Labour, Employment and Skilled Migration in South Africa's 2002 Immigration Act - B.Dodson & J.Crush Managing Relationships in Peripatetic Careers: Scientific Mobility in the European Union - L.Ackers Toward the Analysis of Transnational Social Mobility of Migrant Women: From the Case of the Filipina Domestic Workers - C.Ogaya At the Bottom of the Ladder in the Heath Care Sector: The Impact of Gender, Race and National Origin in Home Health Care in Montreal - D.Meintel, M.Cognet & S.Fortin Settled in Mobility: Transnational Migrants and Gender in Post wall Europe - M.Morokvasic Gender and International Labour Migration: Key Concerns and issues - E.Kofman & P.Raghuram Dialogue Section Upwardly Global: Providing a Nexus for Refugee Professionals and Potential Employers - J.Leu International Convention on Migrant Worker's Rights - N.Piper N.Shah
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.009 |
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".