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Record W4400202542 · doi:10.1108/dprg-10-2023-0150

5G and urban amenity: regulatory trends and local government responses around small cell deployment

2024· article· en· W4400202542 on OpenAlex
James Meese, Kieran Hegarty, Rowan Wilken, Fan Yang, Catherine A. Middleton

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

VenueDigital Policy Regulation and Governance · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAmenitySoftware deploymentContext (archaeology)Government (linguistics)BusinessLegislationPublic administrationRegional sciencePolitical scienceEngineeringGeographyFinance

Abstract

fetched live from OpenAlex

Purpose As part of the 5G rollout, small cell base stations will be deployed across cities. This paper aims to identify an international effort to remove regulatory barriers around deployment and outline emerging strategies Australian local governments are developing to ensure urban amenity in a deregulatory context. Design/methodology/approach This paper analyses existing legislation, policy frameworks and grey literature and has conducted eight interviews with participants from the local government sector. Findings This paper identifies a global deregulatory trend around small cell deployment and that councils are trying to renegotiate their relationship with telecommunications carriers as 5G is rolled out. Three strategies are identified: the design and installation of smart poles, network sharing and partnerships. Originality/value This research contributes to scholarship focused on the 5G rollout and offers one of the first accounts of the emerging tensions between regulatory frameworks, commercial imperatives and municipal authorities, identifying urban amenity as a key area of concern.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.843

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 studies0.0000.000
Scholarly communication0.0010.001
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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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