Recasting Assessment in Continuing Professional Development as a Person-Focused Activity
Bibliographic record
Abstract
ABSTRACT: In this article, we examine assessment as conceptualized and enacted in continuing professional development (CPD). Assessment is pervasive throughout the life of an individual health professional, serving many different purposes compounded by varied and unique contexts, each with their own drivers and consequences, usually casting the person as the object of assessment. Assessment is often assumed as an included part in CPD development conceptualization. Research on assessment in CPD is often focused on systems, utility, and quality instead of intentionally examining the link between assessment and the person. We present an alternative view of assessment in CPD as person-centered, practice-informed, situated and bound by capability, and enacted in social and material contexts. With this lens of assessment as an inherently personal experience, we introduce the concept of subjectification, as described by educationalist Gert Biesta. We propose that subjectification may be a fruitful way of examining assessment in a CPD context. Although the CPD community, researchers, and educators consider this further, we offer some early implications of adopting a subjectification lens on the design and enactment of assessment in CPD.
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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 | 0.030 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".