L'expérience de Gatineau : un exemple d'application du Guide de gestion des documents dans le cadre d'une restructuration municipale
Bibliographic record
Abstract
Dans cet article, les auteurs nous font part des enjeux et des principes qui sous-tendent un processus de fusion et de restructuration municipale. En presentant l'experience de la nouvelle Ville de Gatineau, en Outaouais, les auteurs font un survol des etapes necessaires a la mise en place d'un systeme integre en gestion de documents adapte aux besoins de la nouvelle entite. Pour atteindre leurs objectifs et planifier leurs travaux, les responsables du processus de transition se sont largement inspires du Guide de gestion des documents dans le contexte d'une restructuration municipale. Malgre l'interet de cet outil de travail, les archivistes de la nouvelle Ville de Gatineau ont tout de meme du se questionner sur les differentes options qui se sont presentees a eux tout au long du processus de transition. En effet, malgre les similitudes entre les differentes experiences de restructuration, les auteurs considerent que chacune d'elles revet un caractere distinct. Le contexte regional, la taille des organismes fusionnes et le degre d'implantation des pratiques documentaires sont autant de facteurs rendant chaque experience de fusion unique.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".