Bibliographic record
Abstract
Dans ce chapitre est présenté un bref survol de l’approche de recherche en science du design (RSD) dans la discipline du management. Cette approche de recherche est orientée vers la recherche de solutions à des problèmes de terrain qui auront été convertis en une classe de problème par le manager-chercheur. Ce dernier se donne pour objectif de développer des solutions génériques basées sur l’élaboration de propositions de design qui pourront être mobilisées dans une organisation pour élaborer des solutions précises qui se rapportent à la même classe de problème. Le processus de RSD exige de réaliser quatre grands types d’activités à savoir : 1. L’explicitation de la situation posant problème et sa conversion en une classe de problème générique ; 2. Réalisation d’un état de la connaissance systématique ; 3. Le développement de la solution générique (les propositions de design) ; et 4. L’évaluation de la solution générique (les propositions de design).
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 | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.047 | 0.026 |
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".