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Record W1989763885 · doi:10.1002/smj.2209

Geography and power in an organizational forum: Evidence from the U.S. Senate Chamber

2013· article· en· W1989763885 on OpenAlexaff
Jillian Chown, Christopher C. Liu

Bibliographic record

VenueStrategic Management Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPower (physics)Political scienceManagementEconomic geographyEconomicsPhysics

Abstract

fetched live from OpenAlex

We examine the role that geography plays in structuring interactions within an organizational setting designed to promote broad patterns of interaction: the organizational forum. We propose that, within a forum, an individual's location structures his or her access to peer support, but individuals with power (i.e., those who control the flow of organizational resources) can transcend these geographic constraints. We examine these propositions with data collected on strategic actors in the U.S. S enate C hamber. Using a dyad fixed effects approach, time‐varying controls, selection‐on‐observables estimation, and quasi‐exogenous shocks to seating arrangements, we find support for our propositions. These results contribute to our understanding of strategic interaction patterns, with an emphasis on the geographic scaffold upon which strategic actions are constructed . Copyright © 2013 John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0040.003
Scholarly communication0.0020.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.022
GPT teacher head0.234
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations59
Published2013
Admission routes1
Has abstractyes

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