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Cognition and Beyond: Reviving Individual Persons in Network Reality

2020· article· en· W3045977237 on OpenAlexaff
Qi Zhang, Tiziana Casciaro, David Krackhardt, Gianluca Carnabuci, Brian Philip Reschke, Catherine Shea, Alessandro Iorio, Sameer B. Srivastava, Stefano Tasselli

Bibliographic record

VenueAcademy of Management Proceedings · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOpinion Dynamics and Social Influence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCognitionSocial network (sociolinguistics)Bridge (graph theory)Action (physics)IdeologySociologyPsychologySocial cognitionSocial psychologyPoliticsPolitical scienceLawSocial media

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.284
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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