De l’utilisation de la circularité en MTE : vers un dépassement de la tension entre créativité et rigueur méthodologique
Bibliographic record
Abstract
La méthodologie de la théorisation enracinée est une approche devant permettre de générer des théories innovantes et légitimes d’un point de vue scientifique. Elle peut toutefois faillir à atteindre ces deux objectifs, en particulier à cause de la tension vécue par le chercheur entre créativité et rigueur méthodologique, deux aspects nécessaires pour y parvenir. Nous montrons que cette tension provient du caractère synchrone des processus visant la créativité et la rigueur méthodologique. Cet article expose comment utiliser le caractère circulaire – et non seulement itératif – de la méthodologie de la théorisation enracinée pour rendre asynchrones les processus visant la créativité et ceux visant la rigueur méthodologique et ainsi améliorer la qualité des recherches en MTE.
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 | 0.112 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.045 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".