Community feeling and social interest: Adlerian parallels, synergy and differences with the field of community psychology
Bibliographic record
Abstract
Abstract The field of community psychology has generally elided the insights of depth psychology and the traditions of Freud, Adler and Jung. Implicitly rejecting the notion of the unconscious, community psychology favours conscious, pragmatic agency. Whereas depth psychology is commonly associated with treatment modalities, community psychology argues that psychotherapy is ultimately unnecessary when prevention strategies are adequately deployed. In the critical and community psychology literature psychotherapy is often derided as both ‘individualistic’ and inefficient. Adlerian psychology, which espouses a method of psychotherapy, nevertheless holds key points of synergy with community psychology. To distinguish the school from psychoanalysis Alfred Adler named his approach ‘Individual Psychology’, which could obscure its' social orientation. Like community psychologists, Adlerians similarly argue for a sense of cohesive community as crucial to mental health. They have also adopted an ecological holism as core epistemology, and argue for reducing the necessity of psychotherapy by working in tandem on community‐based prevention strategies. The authors consider the rationale for community psychology's distance from the depth psychologies whilst arguing that the unconscious could, if engaged with analytically, provide the discourse with radical new insights. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".