MétaCan
Menu
Back to cohort
Record W2102702068 · doi:10.1287/orsc.1100.0568

The Missing Link: The Effect of Customers on the Formation of Relationships Among Producers in the Multiplex Triads

2010· article· en· W2102702068 on OpenAlexaff
Andrew V. Shipilov, Stan Xiao Li

Bibliographic record

VenueOrganization Science · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsYork University
Fundersnot available
KeywordsTriad (sociology)BusinessHorizontal and verticalMultiplexAgency (philosophy)Transitive relationMarketingIndustrial organizationPsychologySociologyMathematicsBiologyGeometry

Abstract

fetched live from OpenAlex

This paper develops a concept of a “multiplex triad,” i.e., a triplet composed of actors playing different roles and interconnected by different kinds of relationships. An example of such triad is a social structure comprising two producers connected via horizontal relationships and a customer connected to producers via vertical ties. Multiplex triads are important drivers of network evolution, but their dynamics remains poorly understood. Although conventional wisdom suggests that horizontal ties between producers are driven solely by their prior interactions, we find that vertical ties drive the formation of horizontal relationships in a multiplex triad. We also find that these triads are affected by the agency of the customers who (a) force producers into horizontal relationships with those producers that have protected the customers' interests in the past and (b) prevent closure in triads containing strong horizontal relationships because of the divergent objectives of these triads' members. By drawing attention to the existence of multiplex triads and their underlying dynamics, this paper advances a novel view on transitivity incorporating conflicting interests and agencies of actors within social systems.

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)0.041
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 score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.008
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0220.002

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 head0.242
Teacher spread0.220 · 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

Citations152
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueOrganization ScienceSame topicInnovation and Knowledge ManagementFrench-language works237,207