Les innovations sociales à la lumière de la notion de communautés de personnes
Bibliographic record
Abstract
Les innovations sociales réfèrent à la création et à la mise en œuvre d’idées nouvelles concernant la manière dont les individus devraient organiser des activités interpersonnelles ou des interactions sociales, afin de dégager un ou plusieurs objectifs communs (Mumford, 2002). Ainsi, les innovations sociales concernent ce qui a trait aux personnes et à ce qui les rassemble. C’est pourquoi, il nous a semblé pertinent d’étudier une innovation sociale à la lumière de la notion de communauté de personnes (Melé, 2012), cette notion se distingue à la fois des points de vue individualiste et collectiviste. Pour ce faire, nous avons réalisé une autopraxéographie sur une recherche-action ayant pour objectif la mise en œuvre d’une innovation sociale. Les résultats insistent sur l’importance de favoriser la mise en place de communautés de personnes pour permettre des innovations sociales. Ainsi, cela permet de transformer les cibles de l’innovation sociale en passant d’une cible à trois niveaux (individu, organisation, territoire), à une cible formée de communautés de personnes.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".