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Record W7000437456

Exploration of the views of volunteers in outdoor recreation within a social economy framework / by Carrie McClelland.

2017· dissertation· en· W7000437456 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationSnowball samplingEmpowermentExploratory researchQualitative researchSense of communityLeisure studiesWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Volunteers play a significant role in providing important services to a community. Not only do these services create opportunities for community members to participate in a variety of activities, but they also offer numerous benefits for the individual volunteer. The purpose of this study is to investigate the views of volunteers in outdoor recreation regarding their contributions to community and personal well-being. This topic is
\ninvestigated within a social economy framework in order to effectively understand the place of volunteering in community processes. Using a qualitative approach, 13 exploratory interviews were conducted with outdoor recreation volunteers in Whitehorse during the spring and summer of 2007. The open interview format allowed study participants the freedom to discuss how they felt their volunteer work contributed to their personal well-being, as well as to the greater community. A modified snowball sampling technique was easily applied combining community referrals and systematic cold calling. Interview transcripts were coded to organise passages under common themes. The findings from this study are grouped under five areas of interest; Lifestyle and Sense of Identity, Personal Benefits, Community Benefits, Pressure, and The Influence of Money.
\nIt was found that individuals receive benefits such as increase knowledge, social connections, and empowerment from volunteering in outdoor recreation and that the community receives these benefits through their work. These benefits relate to the social economy through their contributions to community development and exchanges in social
\ncapital.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.060
GPT teacher head0.320
Teacher spread0.260 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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