Authors' reply
Bibliographic record
Abstract
We are pleased that our article has stimulated debate. This was our intention. We are disappointed that some correspondents dismiss our argument by attacking a stereotype of who they think we are or a caricature of what they think we might have said, rather than addressing what we actually did say. Such correspondents have missed, or ignored, the point of the article ? namely, to ask whether the de-medicalisation that has taken place over recent years in British psychiatry is bad for the health of patients and the specialty. We believe this is a question that is worth taking seriously. It is clear from the substantial eletter correspondence and other feedback that many psychiatrists share our concerns and wish for constructive debate. This primary concern with the decline in medical standards of care and the deliberate politicization of debates about service delivery does not imply that we cannot (a) embrace the importance of the full range of biological, psychological and social interventions for psychiatric illness and (b) value our non-psychiatric fellow professionals, and their integral contributions to mental health care. We also believe to be self-evident that services should be informed by the experiences of patients, their relatives and carers and that multidisciplinary team work is crucial for optimal management of psychiatric illness. We are not terribly interested in what is past. We are much more interested to look ahead. Of the wide range of views expressed by respondents, we believe the voice of trainees and those contemplating a career in psychiatry should carry particular weight and we should like to hear more from them. They are the future of British psychiatry.
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 | 0.007 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.045 | 0.039 |
| Insufficient payload (model declined to judge) | 0.019 | 0.011 |
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".