MétaCan
Menu
Back to cohort
Record W3015086528 · doi:10.12775/qs.2020.002

Development and management of outdoor recreation: The case of Quebec

2020· article· en· W3015086528 on OpenAlexafffundabout
Romain Roult, Denis Auger, Jocelyn Garneau, Paul Arseneault

Bibliographic record

VenueQuality in Sport · 2020
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à Trois-RivièresUniversité du Québec à Montréal
FundersUniversité du Québec à Montréal
KeywordsRecreationPromotion (chess)SubsidyGovernment (linguistics)BusinessEnvironmental planningOrder (exchange)Local governmentPerspective (graphical)Environmental resource managementEconomic growthGeographyPolitical scienceEconomicsPublic administrationFinance

Abstract

fetched live from OpenAlex

Outdoor recreation is at the heart of several policies and measures with their goal being to reinforce the level of individuals’ physical activity as well as the development of communities. This is even truer in Quebec where the provincial government recently published (2017) an important note regarding the importance of outdoor recreation in the development of Quebec society. In this perspective, this study, using a quantitative approach through a survey, aims to analyze how outdoor recreation is managed and supported by the Regional County Municipalities (RCM), key actors in the territorial and social development in Quebec, and, to identify the terms and conditions for the practice of these outdoor activities in the RCMs. This study shows that there is no gap between supply and demand. However, the results reveal the importance of supporting and subsidizing promoters and outdoor organizations in Quebec while breaking into segments the pool of practitioners in order to put in place targeted communication and promotion strategies while also promoting the use of new technological information.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.085
GPT teacher head0.376
Teacher spread0.290 · 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 designQualitative
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
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueQuality in SportSame topicRecreation, Leisure, Wilderness ManagementFrench-language works237,207