Bibliographic record
Abstract
Face à l'incertitude suscitée par les crises mondiales, des chercheurs issus de pays francophones d’Europe, du Canada et du Liban cherchent à comprendre les raisons qui motivent les universitaires spécialistes des sciences humaines et sociales à s’engager dans des activités dites d’utilité sociale, ainsi que les conditions de cet engagement. Les trois premiers chapitres analysent les formes d’engagement des universitaires experts dans le contexte de la crise du COVID19, leurs effets sur leurs missions d’enseignement, de recherche et de services et les défis qu’elles soulèvent pour les institutions appelées à devenir capacitantes et apprenantes. Les chapitres suivants portent une attention particulière aux débutants : doctorants et enseignants-chercheurs novices. Ils posent la question, d'une part, de la construction de leur identité de praticiens réflexifs et, d'autre part, des conditions de leur engagement dans des pratiques misant sur les apprentissages des étudiants.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".