Bibliographic record
Abstract
Cet article se réfère à la démarche méthodologique de notre recherche doctorale. Il s’agit d’une recherche qualitative, exploratoire et inductive s’inspirant de la théorisation enracinée (ben Affana, 2008). Dans le cadre de cette étude, nous avons observé une double appropriation, celle d’une technologie et celle d’un processus de discussion et de travail, articulée par des bénévoles québécois et tunisiens luttant contre le sida. Nous avons fait l’hypothèse que les usages déjà acquis par les bénévoles dans leur utilisation des fonctionnalités de l’Internet et leurs pratiques déjà acquises dans leurs expériences d’intervention au sein de leurs organisations communautaires respectives conditionneraient leur appropriation d’un nouveau logiciel (LearningSpace) et d’un nouveau processus de discussion et de travail (penser – agir). L’objectif de cet article est de souligner comment cette double appropriation s’est effectuée à travers des mouvements de construction, de déconstruction et de reconstruction d’un groupe de discussion connecté à divers espaces virtuels (synchrone et asynchrone).
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 | 0.043 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".