MétaCan
Menu
Back to cohort
Record W7099832426

What is the Municipal Potential?*

2002· article· en· W7099832426 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBig Data and Digital Economy
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipGovernment (linguistics)Argument (complex analysis)Local governmentOrder (exchange)Public policy
DOInot available

Abstract

fetched live from OpenAlex

The objective of this paper is to explore the question of the conditions for intergovernmental partnerships through the lens of the changing place of municipalities in the Canadian intergovernmental system. The focus therefore, in the Saskatchewan context, is on partnerships between municipalities and the Saskatchewan government within the broader framework of the federal-provincial relationship. We have traditionally thought of intergovernmental partnerships largely in terms of federal-provincial relations, and the provincial-municipal relationship was seen as one in which provincial government unilaterally shaped and controlled municipal activities. My argument is that we are entering an important transition period in which municipalities are likely to acquire more power and that, in this context, it is important to reflect on how to rethink our views on provincial-municipal relations in line with a partnership model. The perspective taken in this paper is to examine the changing role of municipalities in order to understand the municipal potential for engaging in intergovernmental partnerships. An analysis of the challenges facing municipal governments will lead to an examination of the strengths and limits of municipal governments in the Canadian system and, from this, to an evaluation of their capacity to be effective partners in public policy formulation and implementation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.999

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 communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.042
GPT teacher head0.228
Teacher spread0.186 · 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.

Study designNot applicable
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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicBig Data and Digital EconomyFrench-language works237,207