MétaCan
Menu
Back to cohort
Record W2032188995 · doi:10.1080/23322039.2014.920269

Inter-organizational linkages and resource dependence

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

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.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.093
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
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

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 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

Citations3
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueCogent Economics & FinanceSame topicFirm Innovation and GrowthFrench-language works237,207