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Record W7056655357

Exploring Youth Experiences in Nature Through a Health Equity Lens: A Qualitative Study

2024· other· en· W7056655357 on OpenAlexafffundabout

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2024
Typeother
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsBrock University
FundersCanadian Institutes of Health ResearchBrock UniversityMcGill University
KeywordsQualitative researchReflexivityPhotovoiceThematic analysisEquity (law)Intersection (aeronautics)Health equityPositive Youth DevelopmentFocus groupYouth studies
DOInot available

Abstract

fetched live from OpenAlex

Research demonstrates that for youth, connections to nature are protective health assets and that socio-economic status impacts health outcomes and opportunities. Less is known about how the intersection of youth connections to nature and socio-economic status shape health experiences and findings that do exist are mixed. The purpose of this qualitative study is to understand how youth in the Niagara Region of Canada experience nature, with attention to their socio-economic status. Eight youth between the ages of 11 and 15 were recruited from community organizations and contacts at Brock University and participated in a semi-structured interview. These youth all self-identified as having positive experiences in nature as part of the eligibility requirements for the study. Interviews were audio recorded, transcribed verbatim, and analyzed using reflexive thematic analysis. Two themes were identified from the results 1) connections between nature and participants were strong, regardless of a participant’s socio-economic circumstances and 2) experiences in nature appear to be influenced by SES in terms of the ways youth were able to connect with nature through things like resources and access. Findings are discussed through the lens of the Central Capabilities Approach. A strengths-based approach guided this study.

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)0.007
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0100.007
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.271
Teacher spread0.211 · 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
Published2024
Admission routes3
Has abstractyes

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