Bibliographic record
Abstract
Foreword Information on authors Chapter 1 Introduction and overview of chapters Judy Harris Chapter 2 Different faces and functions of RPL: an assessment perspective Per Andersson Chapter 3 Questions of knowledge and curriculum in the recognition of prior learning Judy Harris Chapter 4 A disciplinary-specific approach to the recognition of prior informal experience in adult pedagogy: 'rpl' as opposed to 'RPL' Mignonne Breier Chapter 5 Portfolio-based assessment of prior learning: a cat and mouse chase after invisible criteria Yael Shalem and Carola Steinberg Chapter 6 RPL and the disengaged learner: the need for new starting points Roslyn Cameron Chapter 7 Beyond Galileo's telescope: situated knowledge and the recognition or prior learning Elana Michelson Chapter 8 Using critical discourse analysis to illuminate power and knowledge in RPL Helen Peters Chapter 9 The politics of difference: non/recognition of the foreign credentials and prior work experience of immigrant professionals in Canada and Sweden Shibao Guo and Per Andersson Chapter 10 RPL: an emerging and contested practice in South Africa Ruksana Osman Chapter 11 'Tools of mediation': an historical-cultural approach to RPL Linda Cooper Chapter 12 Vocations, 'graduateness' and the recognition of prior learning Leesa Wheelahan Chapter 13 Recognising prior learning: what do we know? Helen Pokorny Chapter 14 Reconfiguring RPL and its assumptions: a complexified view Tara Fenwick. Chapter 15 Understanding the transformative dimension of RPL Susan Whittaker, Ruth Whittaker and Paula Cleary Chapter 16 Endword Michael Young Index.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.062 |
| Scholarly communication | 0.017 | 0.028 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 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".