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Record W2993090837

“A place where kids like me can be ourselves”: Exploring the meaning of summer camp with adolescents with neurobiological disorders

2019· dissertation· en· W2993090837 on OpenAlexaboutno aff
Jenna Simpson

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)PsychologySummer campDevelopmental psychologyCommunicationArtPsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

Recreational opportunities are valuable opportunities for physical, social, and emotional development. Summer camp provides youth with the chance to be outside among their peers and learn through play. Unfortunately, social, physical, and institutional barriers often result in the exclusion of high-needs individuals with neurobiological disorders from these camp opportunities and experiences. This research used a qualitative photovoice methodology in order to explore what summer camp means to adolescents with neurobiological disorders.
\nTeens aged 14-17 at Camp Neuro, a sleepaway summer camp in Ontario, were invited to take photographs of things that were meaningful to them (n=23) followed by an individual interview to contextualise the photographs (n=13). Results suggest that the physical, social, and emotional camp environments are important to youth with neurobiological disorders.
\nAdditionally, the opportunity to learn at summer camp was a recurring theme as teens discussed learning skills, learning to make friends, and learning broad life lessons. Overall, the results suggest that youth with neurobiological are successful at summer camp and value their experiences when they are provided with appropriate accommodations and support. Ultimately, the participants expressed that Camp Neuro supported them to ha to be themselves, try new things, and make friends.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.020
GPT teacher head0.224
Teacher spread0.203 · 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.

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
Published2019
Admission routes1
Has abstractyes

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