PLAR: Finding Quality in the Dynamics of Social Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article discusses some of the implications of a recent case study on quality in PLAR for immigrant nurses to Canada. The results reveal complex relations within and across the nursing profession's communities of practice and communities of interest that operate as vehicles for negotiating shared understandings and power. Immigrant nurses who bring knowledge acquired in cultures and educational systems unfamiliar to Canadian authorities stand outside the periphery of the nursing community without a place or voice in the discourse. The author concludes that PLAR can provide a means of giving them voice if nursing stakeholders negotiate a shared understanding of the quality of the process. The author recommends that Baartman et al.'s (2007) quality criteria and concept of assessment in education be explored as a quality framework for anchoring PLAR in nursing registration. Keywords: Prior learning, nursing, quality criteria, community of practice
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.098 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it