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Record W2032188995 · doi:10.1080/23322039.2014.920269

Inter-organizational linkages and resource dependence

2014· article· en· W2032188995 on OpenAlex
Rod B. McNaughton, Brian Paul Cozzarin

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCogent Economics & Finance · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsResource dependence theoryResource (disambiguation)Transaction costExtant taxonAssertionIndustrial organizationBusinessDe factoDatabase transactionPopulationEmpirical researchResource-based viewEconomicsMicroeconomicsMarketingCompetitive advantageComputer scienceStatisticsFinance

Abstract

fetched live from OpenAlex

Few studies have examined the relationship between inter-industry, inter-corporate ownership (ICO) patterns and inter-industry resource exchange patterns. Using data from Statistics Canada, this paper reveals a positive association between the degree of ICO linkages and the degree of input–output dependence among Canadian industry groups. This provides empirical support for the primary assertion of resource dependence theory: that corporations employ ICO linkages to manage their input–output dependence resulting from recurrent resource exchanges. This research differs from extant tests of resource dependence in that it uses data for the population of firms (over a size threshold) in Canada and includes all forms of interdependence between enterprises. The findings suggest scenarios in which corporations can adopt ICO linkages to manage resource dependence and reduce transaction costs.

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)0.000
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 score0.792
Threshold uncertainty score0.846

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)0.0000.001

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 head0.015
GPT teacher head0.186
Teacher spread0.171 · 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