The Development of Social Media Guidelines for Psychologists and for Regulatory Use
Bibliographic record
Abstract
The Association of State and Provincial Psychology Boards, the national organization representing psychology regulatory/licensing boards in Canada and the USA, recently developed social media guidelines that are being recommended for use by its member boards. The purposes of the guidelines were to provide guidance to psychology regulatory boards both countries in identifying and communicating what are considered appropriate and inappropriate uses of social media and to promote consistency and clarity about this across jurisdictions. The process involved reviewing the professional literature, relevant guidelines, standards, current laws, and regulations. The guidelines developed include guidelines about confidentiality, informed consent, risk management, competence, multiple relationships, professional conduct, security of information, personal use of social media, and regulatory board use of social media. Major challenges and limitations in accomplishing this task are identified and discussed.
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 | 0.250 | 0.392 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.014 | 0.014 |
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".