Global Mobility for Psychologists: The Role of Psychology Organizations in the United States, Canada, Europe, and Other Regions.
Bibliographic record
Abstract
Global mobility for psychologists is rapidly improving because of an emerging consensus on recognition standards, the demand for cross-border mobility both internal and external to the profession, and the efforts of membership, credentialing, and regional organizations to promote mobility. In the United States, multiple credentialing organizations promote mobility, primarily through individual endorsement of credentials. The Canadian regulatory boards signed a mutual recognition agreement implementing fast-track mechanisms for licensed psychologists seeking mobility and a competency-based assessment for initial registration. Europe plans to reduce barriers to mobility through mutual recognition of qualifications via a EuroPsy diploma that provides a benchmark for professional psychology education and training. Other regions have not made as much progress with regard to promoting mobility, as many do not yet even regulate the practice of psychology. The authors examine who seeks mobility, which geographic regions promote mobility, and by which mechanisms.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".