Identification et hiérarchisation des critères signifiants au processus de décision, lors d'une demande de financement d'un projet comportant une composante technologique, en Abitibi-Témiscamingue
Bibliographic record
Abstract
Le but de cette étude, de nature exploratoire, est d'identifier les critères simplifiants et présents dans le processus de décision des prêteurs poor une région ressource au Québec. Les résultats générés, à partir des entrevues auprès de 13 analystes financiers d'autant d'organisations distinctes et de plusieurs entrevues auprès de cinq experts, montrent la grande importance des critères informels et la faiblesse de consensus sur une définition commune de ce qu'est un critère informel. On a observé la quasi-absence d'échelle de mesure reliée aux critères informels. La prépondérance des autres critères formels combinés aux critères informels contenus dans un processus type est supportée d'un cadre d'appui qui a fait l'objet de nombreux moments de triangulation et de confirmatioii de la part des répondants.
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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".