Education-Work Relations: Theoretical Reference Points for a Research Domain
Bibliographic record
Abstract
The recent syntheses of research on training at work or the education-work relationship have underlined the difficulty of defining their boundaries (Tanguy 1986; Jobert et al. 1995; Raffe 1995). Different themes demarcate the domain including professional integration, training (educational policy, institutional framework and training programmes) and qualifications. The analytical treatment of the subject is also different in Germany, Great Britain and Italy, because each country experiences specific economic circumstances and institutional modalities particular to their respective education systems (Jobert, Marry and Tanguy 1995). Our approach confirms these diagnostics from another direction.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.008 | 0.059 |
| Scholarly communication | 0.020 | 0.020 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".