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Record W2560102737 · doi:10.1504/ijkbd.2016.10001780

Innovation in the IT sector: intermediary organisations as a knowledge sharing strategy?

2016· article· en· W2560102737 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Knowledge-Based Development · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsUniversité du Québec à MontréalUniversité TÉLUQ
Fundersnot available
KeywordsIntermediaryCONTESTBusinessKnowledge sharingCorporate governanceIndustrial organizationKnowledge economyCompetitive advantageKnowledge managementMarketingMarket economyEconomicsEconomyManagementPolitical science

Abstract

fetched live from OpenAlex

While traditional neoclassical economics view the individual entrepreneur as source of competitiveness, and the market economy as source of economic growth, it has recently been recognised that collective leadership and entrepreneurial activity are often at least as important. Also, knowledge has replaced physical capital as the main source of competitiveness and creation of a competitive advantage over other firms through networks and knowledge sharing. However, it is often unclear how this knowledge can be gained. Some authors contest the neoclassical individualistic view and consider that networks and industrial clusters can foster such knowledge exchanges. We hypothesised that the IT sector would be interested in collective ways of accessing knowledge, and sought to determine what modes of governance or intermediaries could make this happen. The paper analyses these intermediaries and their contributions to the IT/multimedia/gaming sector in Montreal, the cluster policy which favours knowledge exchanges, the collective over the individual.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.279
Teacher spread0.243 · 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