Social Disadvantage is Not Mental Disorder: Response to Campbell-Sills and Stein
Bibliographic record
Abstract
Our target article argued that, although there are genuine social-phobic disorders wherein something goes wrong with mechanisms that generate social anxiety, most conditions satisfying DSM-IV social phobia criteria are likely not disorders but high-end, normal-range social anxiety overstimulated by contemporary social environments that demand high interaction and scrutiny while frowning on submission displays (1). We used the harmful dysfunction analysis of mental disorder to evaluate disorder status: according to this model, a disorder is a harmful failure of an internal mechanism to perform a natural function for which it was biologically designed. Social anxiety, we argued, is a normally distributed, biologically selected trait designed to protect individuals from risky behaviour in the social group. High-end designed levels of social anxiety may be less useful now than in ancestral environments—and even disadvantageous in current social environments—but such anxieties are part of normal human nature and not dysfunctions. In their thoughtful defense of DSM criteria, Campbell-Sills and Stein (2) acknowledge that some community cases of DSM-defined social phobia are normal temperamental variation rather than disorders. Nonetheless, they defend the classification of most DSM social phobia as disorder. They argue that the harmful dysfunction analysis is inadequate for judging disorder; that, anyway, most DSM social phobia is harmful dysfunction; and that, regardless, DSM social phobia is best classified as disorder for pragmatic reasons. We consider these points in turn.
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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 | 0.014 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.037 | 0.070 |
| Insufficient payload (model declined to judge) | 0.003 | 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".