Cognition and Beyond: Reviving Individual Persons in Network Reality
Bibliographic record
Abstract
Network cognition research is gaining increasing prominence in the field of social network. It yields interesting and impactful findings on how network cognition shapes network features, and how they jointly influence key organizational outcomes. In our symposium, we shift the focus from network cognition per se to individual persons in network, reviving the role of the individual person as active perceiverS, interpreters, and actors in shaping network reality. Our four presentations collectively show cognition as one of the mental activities that set the base for individuals’ subjective experience and interpretation of social reality and their further social action of forming or controlling social relations with or among others. We restore both the rational side of individual persons’ seeking influence and mutual understanding, and their seemingly spontaneous side of expressing inner experience and inclination. We also show how micro-level individual mental processes come to serve or constrain relational action and its impact and change macro-level network pattern and eventually the network reality. For Whom is Brokerage a Liability Rather than Advantage? The Cost of Living a Rich Inner Life Presenter: Qi Zhang; Rotterdam School of Management, Erasmus U. Presenter: Stefano Tasselli; Rotterdam School of Management, Erasmus U. Dampening the Echo: Bridge Ideological Network Divides Through Mutual Receptiveness to Opposing View Presenter: Brian Philip Reschke; Brigham Young U. Presenter: Julia Alexandra Minson; Harvard Kennedy School Presenter: Hannah Riley Bowles; Harvard U. Presenter: Mathijs De Vaan; U. of California, Berkeley Presenter: Sameer B. Srivastava; U. of California, Berkeley To Bridge or Not to Bridge? How Power and Status Affect Brokerage Processes Presenter: Alessandro Iorio; Carnegie Mellon U. - Tepper School of Business Presenter: Catherine Shea; Carnegie Mellon U. - Tepper School of Business A Complementary-Supplementary Fit Theory of Network Brokerage Presenter: Gianluca Carnabuci; ESMT Berlin
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.011 | 0.021 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".