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Record W4402303527 · doi:10.59962/9780774870337

Local Governance in Transition

2024· book· en· W4402303527 on OpenAlexaboutno aff
Mary Louise McAllister

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
Fundersnot available
KeywordsTransition (genetics)Corporate governancePolitical scienceBusinessChemistryFinance

Abstract

fetched live from OpenAlex

The early 2020s unleashed a perfect storm on governments worldwide. Logistical challenges never before anticipated left some communities flailing while others thrived. Epidemics, natural disasters, and economic collapses inspired innovation and creativity in many resourceful civic teams. In Local Governance in Transition , Mary Louise McAllister argues that communities wanting to thrive tomorrow must reimagine local governance today. She begins with an overview of how government evolved in Canada, then examines how interdisciplinary initiatives and policies can nudge cities toward a more sustainable future. From coast to coast to coast, environmental change brings existential challenges for Canadian communities. Global awareness and collaboration are key in finding creative solutions for local governance and sustainability. Local Governance in Transition examines systems thinking, environmental studies, and the mechanics of government. Through the adoption of collaborative urban planning and policymaking, and adaptive learning systems, those working in local governance can foster healthier, more resilient communities. This text is for students, leaders, civil servants, and anyone working toward sustainable cities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.335
Threshold uncertainty score0.806

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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