Using discrepancy theory to examine the relationship between shared cognition and group outcomes
Bibliographic record
Abstract
Purpose This empirical study tests hypothesized relationships between team effectiveness and a measure of shared cognition that quantifies the degree of similarity between knowledge of the actual group and beliefs about preferred group states. Design/methodology/approach The proposed model of shared cognition is based upon the triadic structure of actual‐ideal‐ought cognitive representations employed within self‐discrepancy theory. Self discrepancy theory proposes that the degree of discrepancy (similarity) between cognitive representations of the actual self and representations of both the ideal and ought self represents particular emotional situations. This study elevates the concept of a self‐state representation to the group level by asking group members to list attributes associated with the actual, ideal and ought group‐states (group‐state representations). Shared cognition for 56 project teams is measured by comparing the actual group‐state representations of each member with both the ideal and ought group‐state representations of the other members. This extends the measurement of shared cognition beyond the aggregation of individual measures and creates the potential for capturing group level cognition structures that have the potential to evoke affect, influence motivation and impact outcomes. Findings Hypotheses proposing a relationship between team effectiveness and both shared actual‐ideal and shared actual‐ought group‐state representations, mediated by cohesion and confidence in the team's ability, respectively, are mostly supported. Originality/value By examining the degree of similarity between perceptions of what currently exists (knowledge) and what is preferred (belief) this research examines evaluative cognitive structures that have the potential to evoke affect, influence motivation and impact on outcomes.
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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 | 0.015 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".