Les salaires dans le secteur des technologies de l’information et de la communication (TIC): Éléments de comparaison entre le Canada et d’autres pays
Bibliographic record
Abstract
Ce rapport de recherche vise à permettre à TECHNOcompétences de mettre en contexte les résultats du Diagnostic sectoriel du secteur des Technologies de l’information et des communications (2023) mené au Québec, avec la situation ailleurs au Canada et à l’étranger. Pour ce faire, nous identifions différentes sources de données, nous élaborons et appliquons une méthodologie de comparaison des salaires aux occupations du secteur des technologies de l’information et de la communication (TIC) au Canada, aux États-Unis, au Royaume-Uni et à la Suède. Ensuite, nous traitons des limites des comparaisons effectuées en mettons de l’avant les éléments, autres que le salaire, que les employés prennent en compte dans le choix d’un emploi.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".