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Same Governance, Different Day: Does Metropolitan Reorganization Make a Difference?

2004· article· en· W2063403086 on OpenAlexaboutno aff
Laura A. Reese

Bibliographic record

VenueReview of Policy Research · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringConsolidation (business)Corporate governanceMetropolitan areaPoliticsPolitical scienceGovernment (linguistics)Public administrationPolitical economyVariety (cybernetics)Local governmentEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract This commentary focuses on three points related to the debate about urban governmental restructuring: existing conflicts in the literature regarding the outcomes of local government consolidation; insights about consolidation based on an assessment of the amalgamation of twelve municipal units creating the new city of Ottawa; and, a discussion of a variety of methodological and political factors that may well account for the continuing inconsistency in academic assessments of structural change in local government. One possible explanation for the latter conflict is that governmental reorganization does not really make things substantially different in terms of taxes and services, that is, those outcomes most directly experienced by the average citizen. Over the long term other forces, such as intergovernmental relations and the economy, will tend to negate most of the initial effects of change. While there are likely to be winners and losers related to power in government or regime, it will be argued that in large part, for most citizens, governmental reorganization produces the same governance on a different day.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.012
Scholarly communication0.0050.005
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.084
GPT teacher head0.480
Teacher spread0.396 · 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 designObservational
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

Citations33
Published2004
Admission routes1
Has abstractyes

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