Justifying the Diagnostic Status of Social Phobia: A Reply to Wakefield, Horwitz, and Schmitz
Bibliographic record
Abstract
We believe that the harmful dysfunction model is important to consider when defining disorders. However, we question whether, when used in isolation, it provides an adequate basis for discriminating disorders from normal variations of temperament. We believe that it is important to consider the interaction between the individual's temperament and the demands of present-day society. We also assert that, when taken in the aggregate, the DSM-IV criteria for social phobia adequately establish the presence of harmful dysfunctions, particularly when significant impairment in one or more important domains of functioning is present. Finally, we argue that practical issues must be considered when we classify conditions as disorders. The fact that social phobia is classified as a legitimate disorder has undoubtedly spurred research efforts and encouraged countless individuals to seek relief for their suffering.
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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 | 0.012 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.044 | 0.058 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".