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Record W3036626162 · doi:10.1080/02697459.2020.1780386

The Concept and Measurement of Community Well-Being: Lessons for Planners

2020· article· en· W3036626162 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePlanning Practice and Research · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of WaterlooToronto and Region Conservation Authority
FundersNational Research Foundation of Korea
KeywordsWell-beingElement (criminal law)Public relationsPolitical scienceFocus (optics)Public administrationSociologyManagement scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Community well-being is considered a fundamental element of planning practice. However, it is not clear whether, and how explicitly, well-being is addressed in community (i.e. towns or cities) strategies or policy documents. If so, is theconcept used implicitly or explicitly? We reviewed policy documents from the 20 largest individual communities in Canada. Our findings suggest considerable difficulty with translation of data on well-being domains into actionable policy items. Canadian communities tend to focus on traditional, quantitative indicators of well-being. The more nuanced, subjective assessments of well-being are typically not reflected in Canadian communities’ strategies, plans, programs or policies.

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)0.013
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.799
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.578
GPT teacher head0.602
Teacher spread0.024 · 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