CBT accreditation for clinical psychologists: A limitation or an opportunity to apply and maintain our organisational and systemic influence and leadership?
Bibliographic record
Abstract
This paper explains the context for secondary accreditations for clinical psychologists, with a focus on the recognised multi-professional marker for competence in CBT, BABCP accreditation. It describes what CBT accreditation is and how clinical psychologists can achieve it at any stage of their career. The meaning of secondary accreditation within our profession is explored and the debate is outlined in the hope that readers will gain greater clarity about the value and benefits of dual accreditation in CBT for clinical psychologists. The views of clinical psychologists at all stages of their career from trainees to service leads are presented. Recent learning and developments from dual accredited clinical psychology doctorates in England are shared including the voice of a recent graduate of a Level 2 accredited doctorate, to provide insights and guidance for other doctorate programmes currently developing Level 2 BABCP accreditation, their supervisors and their trainees.
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 | 0.029 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".