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Record W2750371184 · doi:10.1177/1078087417722862

Toronto and São Paulo: Cities and International Diplomacy

2017· article· en· W2750371184 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUrban Affairs Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsDecentralizationContext (archaeology)PoliticsPolitical scienceDiplomacyScope (computer science)GlobalizationVariety (cybernetics)Public administrationSubject (documents)Political economySociologyGeography

Abstract

fetched live from OpenAlex

With globalization, the largest cities in the world have been growing in economic importance. And their local powers have often been enhanced as a result of decentralization reforms over the past two decades. In this context, cities—and particularly their mayors—have been reaching out to other cities and jurisdictions to pursue a variety of goals. One term for this process is “paradiplomacy,” but most of the literature on the subject gives little attention to the local political dynamics behind these initiatives. In this article, we explore these local dynamics through a comparison of two major cities, Toronto, Canada, and São Paulo, Brazil. The cases show that external initiatives, both in scope and direction, vary according to the political strategies of the elected mayors. These strategies are strongly affected by the local context and by the political logic of mayoral leadership.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.391
Teacher spread0.355 · 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