A Human Rights-Based Approach to Immigrant Workers: The Policy on Removing the Canadian Experience Barrier
Bibliographic record
Abstract
The Ontario Human Rights Commission’s (OHRC) Policy on removing the ‘Canadian experience’ barrier (CEB)is focused on the strict usage of ‘Canadian experience’ (CE) as an employment or accreditation requirement that raises human rights concerns, and prevents our multicultural society from using the full range of immigrant talents and competencies. The purpose of this paper is to provide an assessment of the OHRC policy initiative as a strategic link between the goals of a skilled labour force and a bias-free workplace, both of which are required to effectively compete in the global economy. This paper argues that making the policy case for the human rights dimensions of social exclusion in hiring is an innovative way to advance creative organizational change that effectively responds to the marginalization and racialization of newcomer populations, by dismantling the chronic rationalization of a harmful workplace practice.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.028 | 0.020 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.020 | 0.014 |
| 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".