Defense Mechanisms and Gender: An Examination of Two Models of Defensive Functioning Derived from the Defense Style Questionnaire
Bibliographic record
Abstract
Different models have been developed to capture an individual’s defensive functioning,\nincluding the DSM-IV Defensive Functioning Scale (DFS). These different models are often\nused to distinguish between psychologically healthy individuals and individuals presenting with a mental disorder, or to demonstrate change in patients over the course of and\nfollowing treatment. Yet, despite evidence that men and women rely on different defence\nmechanisms, most if not all studies into defences rely on the same model for both genders.\nUsing samples of 517 women and 124 men, this study aimed to examine the extent to\nwhich a proxy of the DFS model of defence mechanisms, and the model underlying the\nDefense Style Questionnaire, can be adequately applied to men and women. Confirmatory\nfactor analyses indicated that neither model accurately reflects men or women’s defensive\nfunctioning. Implications of this for research and practice are discussed.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".