‘I Might Be Overqualified’: Personal Perspectives and National Survey Findings on Prior Learning Assessment and Recognition in Canada
Bibliographic record
Abstract
Interest in prior learning recognition among Canadian adults is estimated on the basis of a large-scale national survey and illustrated by an account of the development of a prior learning assessment centre and the individual experiences of participants. Both the common principles and the distinctive activities that characterise the prior learning assessment and recognition (PLAR) field are considered. The survey finds widespread interest in PLAR, especially in the employed labour force, and large unmet demand for both adult education courses and PLAR. There are significant demographic differences: younger adults are much more interested in PLAR regardless of their formal educational attainment, as are non-whites and recent immigrants. Those most involved in informal learning activities have the greatest interest in PLAR, most notably young high school dropouts. Policy implications of these findings and experiences for wider application of PLAR are considered. The direct learner voices quoted in the text can be seen and heard in DVD clips at www.wallnetwork.ca and www.placentre.ns.ca .
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".