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Record W4413369228 · doi:10.1080/14729679.2025.2547232

The potential of outdoor education experiences for autistic girls: a narrative literature review

2025· article· en· W4413369228 on OpenAlexaff
Elena Groen-Sylvester

Bibliographic record

VenueJournal of Adventure Education & Outdoor Learning · 2025
Typearticle
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOutdoor educationNarrativePsychologyAdventure educationAutismPedagogyDevelopmental psychologyNarrative inquirySociologyArtLiterature

Abstract

fetched live from OpenAlex

Autistic girls are a marginalized and under-supported population. This is especially evident in the field of outdoor education, where inclusion of autistic girls as research participants is almost non-existent. Utilizing critical disability theory as a framework, this narrative literature review sought to address this gap by combining two areas of research: outdoor education and autism and autistic girls and self-concept. The analysis of the literature was completed through reflexive thematic analysis, with the purpose of generating themes that contribute to understanding the potential benefits and drawbacks of outdoor experiences for autistic girls. The themes that emerged included the importance of belonging and relationships, the influence of external factors on play experiences, and the positive shift in self-perception achieved through overcoming manageable challenges.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.346
Teacher spread0.340 · 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 designNot applicable
Domainnot available
GenreReview

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 routes1
Has abstractyes

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