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Record W2949713492

Improving the management of intergovernmental relations: a project for the City of St. Albert government relations committee

2019· article· en· W2949713492 on OpenAlexaboutno aff
Trevor W Duley

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLeadership, Human Resources, Global Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsPublic administrationGovernment (linguistics)Political scienceManagementRegional scienceSociologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Regional and intergovernmental structures and dynamics are changing at a local government level in Alberta because of legislated collaboration frameworks and growth management boards, starting in 2008 and enhanced in 2017. For the City of St. Albert, who is impacted by this, it is becoming increasingly challenging to approach intergovernmental matters in a coordinated manner, and to maintain existing service- levels related to intergovernmental administrative services. One option to improve the situation, could be the development of a Government Relations Council Committee, as has been done elsewhere in Western Canada. The purpose of this report is to look at if a Government Relations Committee is a viable option for the City of St. Albert, by looking at the literature around municipal intergovernmental structures and practices in Western Canada, and by surveying the same municipalities. The research question is: if the City of St. Albert were to pursue the development of a Government Relations Committee, what would be the framework for its development?

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)0.015
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.114
Threshold uncertainty score0.828

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0320.007
Scholarly communication0.0110.003
Open science0.0030.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.033
GPT teacher head0.280
Teacher spread0.246 · 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 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
Published2019
Admission routes1
Has abstractyes

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