Self-Efficacy, Values, and Complementarity in Dyadic Interactions: Integrating Interpersonal and Social-Cognitive Theory
Bibliographic record
Abstract
Dyadic interactions were analyzed using constructs from social-cognitive theory (self-efficacy and subjective values) and interpersonal theory (interpersonal circumplex [IPC] and complementarity). In Study 1, the authors developed a measure of efficacy for interpersonal actions associated with each IPC region--the Circumplex Scales of Interpersonal Efficacy (CSIE). In Study 2, the authors used the CSIE and the Circumplex Scales of Interpersonal Values (which assesses the subjective value of interpersonal events associated with each IPC region) to predict the dominance expressed and satisfaction experienced by members of 101 same-sex dyads trying to solve a murder mystery. Structural equation modeling analyses supported both social-cognitive and interpersonal theory. A social-cognitive person-variable (dominance efficacy) and an interpersonal dyadic-variable (reciprocity) together predicted dominant behaviors. Likewise, both a social-cognitive variable (friendliness values) and an interpersonal variable (correspondence of friendliness efficacy) predicted satisfaction. Finally, both shared performance outcomes and dynamic interpersonal processes predicted convergence of collective efficacy beliefs within dyads.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".