Building Flexibility and Accountability Into Local Employment Services: Country Report for Belgium
Bibliographic record
Abstract
Human resources and skills are becoming increasingly important to economic development. In the context of the economic downturn, challenges such as high youth unemployment call for a collaborative approach between local employment officials, educational institutions and wider social and economic partners. But do local labour market offices have sufficient flexibility in the implementation of their policies and programmes to contribute effectively to local strategies? If local labour market offices are to be given more flexibility, how can this be reconciled with the need for accountability and the achievement of national policy goals?The Belgium case study for the Building Flexibility and Accountability into Local Employment Services project explores the level of local accountability and flexibility within labour market policy in Flanders, focusing in particular on the Flemish Public Employment Service (VDAB), municipalities and the regional tripartite consultation platforms SERRs and RESOCs. This report is one of four country reports, with the other participating countries being Canada, Denmark and the Netherlands. A synthesis report is also available (see Working Paper 2011/10).
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".