The politics of difference: non/recognition of the foreign credentials and prior work experience of immigrant professionals in Canada and Sweden
Bibliographic record
Abstract
The recognition of prior learning (RPL) is an educational response to the need to widen participation in education and training for economic advancement and social inclusion. The social meanings of RPL have different configurations depending on historical, cultural, economic and political forces in different places. One constant is the reliance on the widely pervasive educational philosophies of experiential learning: constructivism and progressivism. This book challenges the orthodoxy of experiential learning and the particular readings of knowledge, pedagogy, learning, identity and power which it privileges. It does this by introducing different theoretical resources to RPL and drawing on experiences of RPL in the UK, the USA, Canada, South Africa, Australia, and Sweden. The book provides a range of re-conceptualisations of the relational terrain between adult experience and learning on the one hand, and specialist or academic knowledge on the other.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.020 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".