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A tale of two cities: urban mental health in Vancouver and New York City

2019· book-chapter· en· W2954239584 on OpenAlexaboutno aff
Kerry L. Jang, Michael Krausz, Michael Jae Song

Bibliographic record

VenueOxford University Press eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsStatutory lawLocal governmentState (computer science)UrbanizationPublic administrationGovernment (linguistics)Order (exchange)Service (business)BusinessMental healthMunicipal servicesEconomic growthPolitical scienceEconomicsFinanceLawMedicine

Abstract

fetched live from OpenAlex

Urbanization and mental health are inter-linked. With the expansion of cities, pressures on services are increasing. The constraints for providing healthcare services are tremendous and financial resources can be demanding. In this chapter, service provision in Vancouver and New York are compared. It is well recognized that in most countries, there exist three levels of government: the national or federal, state or provincial assemblies, and city or municipal councils. In theory, each order is relatively independent. Local or municipal governments typically derive their powers from state or provincial law. This is notable because it places statutory limitations on what cities are responsible for, and restrictions on how, and where, the municipality may raise and spend monies. Health care policies may be developed at federal or national levels and, paradoxically, their delivery is expected at local levels, raising specific issues and pressures on local authorities.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.180
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0080.002
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.002

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 head0.036
GPT teacher head0.251
Teacher spread0.215 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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