Making sense of board effectiveness: a socio-cognitive perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – This paper aims to investigate a team dynamics based approach to assess board effectiveness, namely the interplay between boardroom decision-making processes and the board members' cognitive mental models. Design/methodology/approach – A socio-cognitive perspective is utilized for analyzing board processes and determining board effectiveness. Utilizing the concepts of team mental models and sensemaking, a theoretically grounded model of board effectiveness is developed, wherein the propositions predict the causality and effect of the socio-cognitive and sensemaking processes on board effectiveness. Findings – The proposed model is able to analyze the relationship among the different decision-making processes and members' cognitive models as determinants of board effectiveness, wherein the board's decision making process mediates the board's cognitive model – effectiveness relationship, while the board's cognitive model moderates the decision process – effectiveness relationship. Research limitations/implications – The conceptual model advances a rationale that might explain the mixed or modest findings in literature on the relationship between board demographics, dynamics and effectiveness. Practical implications – The model allows practitioners and policy makers an alternative mechanism to assess board effectiveness, that is able to not only integrate the demographic, diversity and dynamics related measures, but also enables a clear understanding of the cognitive influences on board decision making and effectiveness. Originality/value – The conceptual model encompasses most of the relevant constructs and findings of previous studies and offers a parsimonious yet holistic understanding of the boardroom mechanisms that might determine board effectiveness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it