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Record W4402516309 · doi:10.1080/14729679.2024.2403022

Social media as a learning resource for outdoor enthusiasts: a Canadian perspective

2024· article· en· W4402516309 on OpenAlex
Charlotte Huebner, Christian Mercure, Tegwen Gadais

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

VenueJournal of Adventure Education & Outdoor Learning · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversité du Québec à ChicoutimiUniversité du Québec à Montréal
Fundersnot available
KeywordsOutdoor educationPerspective (graphical)Social mediaSociologyResource (disambiguation)PsychologyPedagogyVisual artsComputer scienceArt

Abstract

fetched live from OpenAlex

Outdoor enthusiasts can acquire knowledge and skills about their activities in different ways, one of these being social media. Nonetheless, there is limited scientific literature that allows us to understand how outdoor enthusiasts currently use social media to learn about their activities. This exploratory research, based on a mixed method design, aims to better understand how Canadian outdoor enthusiasts (COE) use social media to learn about their outdoor activities. This study examined how 368 COE use social media to learn about their activities. Chi-square tests and t-tests were applied to analyze differences between participants’ answers and individual characteristics. Results suggest that COE do indeed use social media to learn about their activities. Qualitative data originating from the same survey suggests that COE also use social media to get ideas and inspiration as well as to connect with other outdoor enthusiasts.

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)0.002
metaresearch head score (Gemma)0.009
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.015
GPT teacher head0.353
Teacher spread0.338 · 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