In search of integrated specificity: Comment on Denson, Spanovic, and Miller (2009).
Bibliographic record
Abstract
Psychologists have long been interested in the integrated specificity hypothesis, which maintains that stressors elicit fairly distinct behavioral, emotional, and biological responses that are molded by selective pressures to meet specific demands from the environment. This issue of Psychological Bulletin features a meta-analytic review of the evidence for this proposition by T. F. Denson, M. Spanovic, and N. Miller. Their review concluded that the meta-analytic findings support the "core concept behind the integrated specificity model" (p. 845) and reveal that "within the context of a stressful event, organisms produce an integrated and coordinated response at multiple levels (i.e., cognitive, emotional, physiological)" (p. 845). I argue that conclusions such as this are unwarranted, given the data. Aside from some effects for cortisol, little evidence of specificity was presented, and most of the significant findings reported would be expected by chance alone. I also contend that Denson et al. failed to consider some important sources of evidence bearing on the specificity hypothesis, particularly how appraisals and emotions couple with autonomic nervous system endpoints and functional indices of immune response. If selective pressures did give rise to an integrated stress response, such pathways almost certainly would have been involved. By omitting such outcomes from the meta-analysis, Denson et al. overlooked what are probably the most definitive tests of the specificity hypothesis. As a result, the field is back where it started: with a lot of affection for the concept of integrated specificity but little in the way of definitive evidence to refute or accept it.
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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 | 0.017 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.047 | 0.051 |
| Insufficient payload (model declined to judge) | 0.009 | 0.010 |
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".