LEMIRE (Louise) , PROULX (Denis) , COOREMANS (Luc) , Modernisation de l’État et gestion des ressources humaines. Bilan et perspectives Québec-Belgique , Québec, Athéna éditions, 2005,250 p.
Bibliographic record
Abstract
Representation Problems in New Caledonia’s Civil Service The author examines whether New Caledonia’s civil service is representative of the territory’s national and ethnic groups, and whether there is any demand for greater representation. This study on civil service officials (for whom it is difficult to obtain reliable information) suggests that this is not generally the case. It also includes an analysis of their legal status, although specific provisions only concern minor matters. New Caledonia’s civil service is currently affected by two dynamic factors : firstly, the need to “achieve a new balance” in accordance with the Preamble of the Nouméa Accord, and secondly, the need to give local people priority access to jobs. The achievement of a new balance has an ethnic dimension, but it is not strong enough to foster the emergence of a representative civil service. Furthermore, giving local people priority access to jobs seems to go against such a development.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 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".