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Record W4386148273 · doi:10.1080/11745398.2023.2250477

Supporting rural low-income families: a municipal recreation department's response to community crisis

2023· article· en· W4386148273 on OpenAlexafffundabout
Jackie Oncescu, Megan Fortune, Laura Fisher, Mary Sweatman, Julia Frigault

Bibliographic record

VenueAnnals of Leisure Research · 2023
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsAcadia UniversityUniversity of New Brunswick
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRecreationEconomic growthWork (physics)Political scienceSocioeconomicsSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

Recreation is an important resource that can support residents’ capacity to cope with stress and deal with community crisis, such as a pandemic. However, rural low-income families often experience inequitable access to recreation provisions. COVID-19 pandemic forced municipal recreation departments across Canada to re-evaluate and adapt their provisions, of particular importance for rural low-income families. Through the lens of social liberalism, this study examined the role of a municipal recreation department's response to community crisis and the implications of its provisions on rural low-income mothers and their families’ capacity to facilitate leisure during the pandemic. Through 29 interviews with low-income mothers and a focus group with the recreation department, we illuminate how provisions were designed and delivered to address income inequality, geographic isolation, social exclusion and childcare. Considering these findings, we discuss the department's approach to redesigning and delivering provisions and the implications to supporting low-income families’ access to recreation.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.229
GPT teacher head0.527
Teacher spread0.299 · 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.

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

Citations3
Published2023
Admission routes3
Has abstractyes

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