Constructing the IT skills shortage in Canada : the implications of institutional discourse and practices
Bibliographic record
Abstract
5. These discourses are consistent with institutional theory, which suggests that certain practices may become widespread and "taken-for-granted " regardless of their link to actual performance or outcomes. The unintended consequence is systemic discrimination. Building on previous work, this paper explores systemic barriers to women in information technology professions by focusing on the ways in which institutional practices reinforce a definition of "information technology professional " that tends to exclude women. It examines the recent discourse on the "Information Technology Skills Shortage " in selected texts from industry, professional associations, academia and programs aimed at increasing the participation of women, focusing on the implications of discursive practices for the inclusion of women. In particular, it examines some of the apparent inconsistencies and contradictions which appear in the institutionalized discourse and practices.It argues that: 1.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.051 | 0.050 |
| Scholarly communication | 0.025 | 0.007 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".