Developing and implementing a continuing competence program for professional psychologists: A Canadian perspective
Bibliographic record
Abstract
This paper was included in a unique “ethics track”, which was a first for this conference. Historically, they have not grouped series of papers this specifically and my talk followed some “heavyweights” in the field of psychology and ethics from Canada, the U.S., Africa, and Europe. The source of the material for the paper was a 7 year project of the College of Alberta Psychologists and I was a key leader in its inception, development and implementation over this time, including serving as President of the College in the year that this project came to fruition. Several key issues help place the reaction to this work in context. First, the continuing competence program referred to in the title is now in place. It took 7 years of development in this phase of development, but the movement and impetus for this type of program has been brewing since 1972. It has continually been derailed by the professional membership of the College for many, mainly political, reasons. Due to changes in Alberta’s Health Professions Act, it is now mandatory to have such a program. What sets the program apart from others is a philosophical position that moves the responsibility for self-development as a professional from the regulator to the psychologist. Other systems have the regulator track continuing education credits whereas this system has the professional self-determine the activities for the year and track them as they are completed.
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 | 0.032 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.036 | 0.015 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 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".