Recruiting Talent in the Information and Communications Technology (ICT) Sector: What Role for Immigration?
Bibliographic record
Abstract
Immigration has played a critical role in the growth of the Canadian Information and Communications Technology (ICT) sector over the past two decades. In the face of declining domestic post-secondary education enrollment rates in ICT fields of study, it appears that further ICT sector expansion will continue to rely heavily on sources of foreign-educated workers. This report provides a broad discussion of the main challenges the government faces in providing an immigration system that will meet the future needs of the sector, not only in terms of filling existing labour market shortages, but also in term of proactive policy enabling employers to compete for the world's most talented high-tech workers, thereby putting Canada in a position to be an international leader in ICT. In addition, it describes key recent changes in Canada's permanent and temporary immigration programs of relevance to the ICT sector, in each case emphasizing to what extent the programs are likely to address the policy challenges facing the sector.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".