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Record W4399754046 · doi:10.1111/capa.12570

5G implementation and multi‐level governance: The case of Quebec municipalities

2024· article· en· W4399754046 on OpenAlexaffabout
Jérémy Diaz, Sandra Breux, Nathan Mascaro, Marie‐Soleil Cloutier

Bibliographic record

VenueCanadian Public Administration · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCorporate governanceMulti-level governanceRegional scienceEnvironmental planningBusinessPolitical scienceGeographyPublic administrationFinance

Abstract

fetched live from OpenAlex

Abstract Municipalities are often considered to be places of innovation. However, certain issues, such as 5G, suggest that the municipal level of government is hampered by challenges. In this article, we present the results of a survey of 220 respondents from 54 different municipalities of various sizes, alongside a media press review. We show that 5G is indicative of the challenges pertaining to multi‐level governance, the presence of a significant information deficit as well as the clout of the private sector in public planning. These findings call on us to examine municipal governance and the relevance of creating intermunicipal cooperation.

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)0.002
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 score0.919
Threshold uncertainty score0.587

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0120.003
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.266
Teacher spread0.216 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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