Information and Communication Technology Talent: The Skills We Need—Framing the Issues
Bibliographic record
Abstract
This article provides a conceptual framework for discussing information and communication technology (ICT) skills shortages in a context in which having a sufficient supply of skilled ICT workers—both inside the ICT sector and more broadly—is critical to the performance of the Canadian economy. We start with an outline of a simple model of how ICT skills shortages might be manifested in labour market signals, such as rising wages, and then how, in response to these signals, workers already in the labour market should adjust, whereas young people making schooling and career decisions would be expected to skew toward ICT areas. We then discuss some of the reasons these dynamics might not follow this model, and therefore how ICT skill shortages could potentially endure over time. The article sets the stage for the other articles in this special issue, which address these and other issues related to ICT skills from a mix of traditional academic and industry perspectives.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.045 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".