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Record W2121402323 · doi:10.1287/mnsc.1110.1507

Firm Survival and Industry Evolution in Vertically Related Populations

2012· article· en· W2121402323 on OpenAlex
John M. de Figueiredo, Brian S. Silverman

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

VenueManagement Science · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUpstream (networking)Corporate governanceDownstream (manufacturing)Industrial organizationAffect (linguistics)Upstream and downstream (DNA)Vertical integrationBusinessMarketingTelecommunicationsSociologyEngineering

Abstract

fetched live from OpenAlex

This paper examines how the density and governance of vertically related populations affect the life chances of organizations. We integrate the literatures on organizational ecology and vertical integration to develop a theory of how (1) specialized upstream industries affect downstream survival rates, (2) the prevalence of different governance forms among upstream and downstream organizations moderates this relationship, and (3) different forms of governance exert differential competitive pressures on focal organizations. We find evidence supporting our hypotheses in an empirical examination of the downstream laser printer industry and upstream laser engine industry. This paper was accepted by Jesper Sørensen, organizations.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.051
GPT teacher head0.253
Teacher spread0.202 · 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