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Record W2127111868 · doi:10.1177/0010414008328635

The Role of Interfirm Networks in Technological Innovation and Education

2008· article· en· W2127111868 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComparative Political Studies · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Policies and Impacts
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInefficiencyInvestment (military)Human capitalEconomicsBusinessIndustrial organizationTechnological changeLabour economicsMarket economyEconomic systemMacroeconomics

Abstract

fetched live from OpenAlex

This article examines the sociopolitical conditions for preventing market failure in public goods investment. Based on International Social Survey Program data for 17 advanced industrialized countries, the author compares economies with strong and weak institutions of interfirm coordination in how they encourage investment in skills and technological innovation and highlight the inefficiency of alternative investment strategies that bypass cooperation. With weak coordination, firms underinvest in skills and the labor market relies on academic education as an alternative, resulting in underutilization of human capital. Innovation intensifies skill demands and can reduce overeducation. However, without cooperation, firms also underinvest in research and development, and the economy relies on innovation from outside the firm, which reduces its effectiveness in alleviating overeducation. In countries with weak interfirm coordination, the economy suffers simultaneously from deficient skills, underused academic qualifications, and technological innovations with limited human capital benefits for the labor force.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.244

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.133
GPT teacher head0.323
Teacher spread0.190 · 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