Engaging Health Professionals Toward the Redevelopment of a Continuing Competence Program
Bibliographic record
Abstract
Continuing competence is the combination of knowledge, skills, abilities, and judgment of a professional, applied safely and ethically to their practice of the profession. Under the Health Professions Act in Alberta, health regulatory colleges must oversee the continuing competence of their registrants, ensuring they act in the public’s best interest. At Health Professionals Regulatory College (HPRC), over 3500 registrants are accountable to its continuing competence program (CCP). The current CCP, in place for over 15 years, has not integrated collection and analysis of diversity data that may influence individual competence, nor has it evolved with trends toward right-touch regulation that encourage data-informed, risk-based approaches to regulation. This organizational improvement plan (OIP) establishes the organizational context of HPRC within a structural-functional environment and applies critical theory to address the identified problem of practice (PoP)—the lack of a reflective and responsive CCP. A future CCP is envisioned to support ongoing practitioner learning, promote better practitioner-college relationships, increase confidence and status of the profession, and improve patient outcomes. Acknowledging that redevelopment of the CCP involves an emergent change process, the OIP focuses on rethinking the CCP as the first of three change cycles. Combined with an authentic leadership approach, appreciative inquiry is the selected change model to implement a strategy that balances top-down and bottom-up approaches, aiming to optimize stakeholder diversity and meaningful participation. Detailed plans for change implementation, communication, and monitoring and evaluation are outlined. The OIP concludes with thoughts on next steps for CCP redevelopment and future considerations for HPRC.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".