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Record W2297796838 · doi:10.1287/orsc.2016.1057

Inside the “Hybrid” Iron Cage: Political Origins of Hybridization

2016· article· en· W2297796838 on OpenAlex
Tai Young Kim, Dongyoub Shin, Young‐Chul Jeong

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOrganization Science · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsConcordia University
Fundersnot available
KeywordsPresidential systemPoliticsSettlement (finance)Organizational structureVotingPower (physics)Selection (genetic algorithm)Balance (ability)Social movementSociologyPolitical sciencePublic relationsEconomic systemPolitical economyBusinessEconomicsComputer sciencePsychologyLaw

Abstract

fetched live from OpenAlex

This paper examines how social-movement-type political interactions between conflicting parties within an organization influence the adoption of a hybrid practice. We argue that a hybrid practice is likely to be adopted when power balance between challengers and incumbents is achieved. To shed light on conditions for organizational settlement based on such power balance, we focus on three factors: structures, actors, and processes of social-movement-type political interactions within organizations. By studying changes in the presidential selection systems of Korean universities between 1988 and 2006, this paper illustrates how organizational settlement resulted in the adoption of a hybrid system by combining elements of two previous competing presidential selection systems—appointment and direct voting systems. The general implications for the understanding of hybridization, organizational settlement, and organizational heterogeneity are discussed.

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.

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)0.001
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 score0.718
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.002
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 head0.018
GPT teacher head0.242
Teacher spread0.223 · 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