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Knowledge‐Intensive Business Services and Regional Development: Strategic Importance of

2017· other· en· W4248270691 on OpenAlexaff
Richard Shearmur

Bibliographic record

VenueInternational Encyclopedia of Geography · 2017
Typeother
Languageen
FieldSocial Sciences
TopicRegional Development and Policy
Canadian institutionsMcGill University
Fundersnot available
KeywordsBusinessKey (lock)Face (sociological concept)Industrial organizationKnowledge managementEconomic geographyEconomicsComputer science

Abstract

fetched live from OpenAlex

Knowledge‐intensive business services (KIBS) have emerged as a key sector in the knowledge economy, both as conveyors of expertise and as vectors of information exchange playing an important – but sometimes underappreciated – role in innovation dynamics. They can contribute to the economy directly by exporting, and indirectly by assisting other economic actors in their export‐oriented business activities. A key question has been, and remains, the extent to which local economies require KIBS in their midst or can benefit from KIBS imported from other regions. Attracting and retaining KIBS locally may seem attractive to regions seeking to diversify their economies and enhance their local innovation systems, but it is far from certain that such a strategy is feasible or likely to succeed: local establishments may benefit more from interacting with specialized KIBS in other regions (often cities), and new communications technologies, combined with intermittent face‐to‐face meetings, are making this increasingly possible.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.644
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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