Penuries de main-d'oeuvre qualifiee et adoption des technologies de pointe
Bibliographic record
Abstract
Le present document vise a determiner dans quelle mesure les etablissements du secteur canadien de la fabrication font face a des penuries de main'd'oeuvre qualifiee et, le cas echeant, si ces penuries semblent nuire a l'adoption des technologies de pointe. Les usines qui adoptent des technologies de pointe declarent des penuries, particulierement chez les professionnels, comme les specialistes des sciences et les ingenieurs, et chez les specialistes techniques. Les problemes qu'entrainent ces penuries sur le marche du travail dependent pour une large part des solutions adoptees par les etablissements qui y font face. Le present document demontre que les penuries de main-d'oeuvre qualifiee ne semblent pas nuire a l'adoption des technologies, etant donne que les etablissements qui declarent des penuries sont aussi ceux qui sont les plus avances au niveau technologique. Meme s'ils font face a des besoins plus grands de main-d'oeuvre qualifiee, ils semblent etre en mesure de resoudre les penuries qui se posent.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".