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Record W2140716920 · doi:10.47678/cjhe.v44i2.183813

Partnering for economic development: How town-gown relations impact local economic development in small and medium cities

2014· article· en· W2140716920 on OpenAlexvenueaboutno aff
Jennifer Massey

Bibliographic record

VenueCanadian Journal of Higher Education · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)Local economic developmentExperiential learningEconomic growthCommunity developmentHigher educationSocial capitalEconomic impact analysisPolitical sciencePublic relationsSociologyPedagogyEconomicsSocial science

Abstract

fetched live from OpenAlex

Universities play an increasingly prominent role in shaping regional, social, and economic development. In Canada, however, spatial, economic, and social differences between universities and their host communities continue to challenge positive town–gown relationships and undermine the benefits associated with high concentrations of prospective young, “creative” graduates. The purpose of this article is to identify the factors that lead to positive town–gown relations and, subsequently, encourage graduate retention. Through this research, university and town administrators were found to play a key role in establishing a positive relationship between students and community members. Local employment opportunities were also found to help students build an experiential relationship with their localities and make them more likely to settle there after graduation.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0070.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.043
GPT teacher head0.287
Teacher spread0.244 · 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 designQualitative
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

Citations22
Published2014
Admission routes2
Has abstractyes

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