Renforcer son impact social grâce à l’économie circulaire : le cas de l’organisme d’insertion socioprofessionnelle Insertech
Bibliographic record
Abstract
Ce cas présente l’expérience d’Insertech, une organisation d’économie sociale, dont la mission est d’aider les personnes éprouvant des difficultés à intégrer ou à réintégrer le marché du travail, tout en prolongeant la durée de vie du matériel informatique. Cet organisme d’insertion socioprofessionnelle a choisi d’allier une vocation environnementale à sa mission sociale à travers la réparation d’ordinateurs, luttant ainsi contre le gaspillage des ressources et contribuant à réduire la quantité de déchets électroniques envoyés à l’enfouissement. Le cas identifie les apports de cette organisation qui contribue à l’ancrage territorial en maintenant et en développant des ressources humaines locales par la formation, par l’insertion professionnelle et par la mobilisation de stratégies circulaires de reconditionnement et de réemploi.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".