Remediation in Practice: A Polarity to be Managed
Bibliographic record
Abstract
ABSTRACT: Originally developed in the business literature, a polarity is a concept where 2 distinctive and opposing characteristics (poles), each presenting advantages and disadvantages or opportunities and pitfalls, must both be taken into account to ensure effective management of a challenging problem. Managing a polarity is a thorny endeavor because it entails striving to maximize the benefits of both poles while simultaneously minimizing or controlling the downsides of each. Previous investigations into stakeholder conceptualizations of remediation led us to suggest that remediation is framed in stakeholders' minds simultaneously as an educational endeavor (ie, the remediatee needs educational support to regain full competence) and a regulatory act (ie, the revocation of the individual's professional right to self-regulate their practice and learning). In this article, we argue that viewing remediation for practicing physicians as a polarity to be managed offers a framework that can further the conversation about how to address some of remediation's challenges.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.067 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.009 | 0.011 |
| 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".