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Record W4415587135 · doi:10.21083/crrf.v27i1.8638

The Trout Creek Community Centre: A space for sport, recreation, and resiliency

2025· article· W4415587135 on OpenAlexaffabout
Kyle Rich, Laura Misener, Trout Creek Community Center Board

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsWestern University
Fundersnot available
KeywordsRecreationPrideTroutCommunity organizationSpace (punctuation)Corporate governanceProcess (computing)Expression (computer science)

Abstract

fetched live from OpenAlex

The community of Trout Creek, Ontario, located approximately three hours north of Toronto is home to about 600 residents. In the early 2000’s the community experienced dramatic change in several ways. In three years, a highway bypass drastically changed the economic opportunities in the community; the local school was closed by the regional school board, and; the community was amalgamated with a neighbouring community and municipality. In this presentation, we will discuss a case study examining the role that the management of sport, recreation and the community centre played in the process of community resiliency. Specifically, we will discuss the governance of sport and facility management in the community and how the collective actions of the community were enabled through these activities. We argue that the management of sport and recreation in the community allowed for the expression of characteristics (e.g., leadership, togetherness, and problem solving) identified by Kulig, Edge, and Joyce (2008), which may facilitate community pride and sense of belonging indicative of the expression of a sense of community. Our analysis suggests that sport management in rural contexts may have important implications for the process and development of community resiliency.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Canadian Rural Revitalization FoundationSame topicRecreation, Leisure, Wilderness ManagementFrench-language works237,207