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Record W2143862569 · doi:10.1177/0020715212460257

Varieties of corporate networks: Network analysis and fsQCA

2012· article· en· W2143862569 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Comparative Analysis Research
Canadian institutionsnot available
FundersMinisterio de Ciencia y Tecnología
KeywordsQualitative comparative analysisTypologyUnificationInterlockBusinessIndustrial organizationCohesion (chemistry)DecentralizationComputer scienceEconomicsSociologyEngineering

Abstract

fetched live from OpenAlex

The present research analyzes national corporate interlock networks and their causal conditions. The objective is two-fold: 1) to specify types of corporate networks, and 2) to pinpoint the causal configurations that give rise to each type of corporate network. First, corporate networks on basis of interlocking directorates are analyzed and compared using social network analysis to empirically derive a typology. The results show two types of corporate networks: cohesive corporate networks which are based on unification, centralization and strength ties; and dispersed corporate networks which are characterized by fragmentation, decentralization and single ties. Second, combinations of causal conditions that explain the emergence of each type of corporate networks are identified using fuzzy set qualitative comparative analysis (fsQCA). Finally, avenues of research on corporate interlock networks are suggested.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.166
GPT teacher head0.477
Teacher spread0.311 · 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