The Impact of Winning and Losing on Family Interactions: A Biological Approach to Family Therapy
Bibliographic record
Abstract
OBJECTIVE: To examine the connection between winning and losing and family functioning. We do this by hypothesizing a link between successful outcomes in individual competition and in functional family interaction. This enables us to show how therapeutic interventions can be directed toward the attachment system, by lowering anxiety and fostering mutual trust, and toward the social rank system, by promoting success and feelings of empowerment. METHOD: A search of online databases was conducted with key search terms related to winning and losing, and their effects on attachment patterns and family interactions. RESULTS: Winning in agonistic encounters has been associated with lowered dysphoria, anxiety, and hostility. These affective states trigger positive patterns of family interaction through their effect on the social rank and attachment systems. CONCLUSION: Continued success promotes adaptive cycles of interaction, whereas inability to accept loss has the reverse effect. Early humans, who were more successful in competition, were better able to promote the survival and well-being of other family members, which would have accelerated our phylogenetic adaptation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".