MétaCan
Menu
Back to cohort
Record W4414402524 · doi:10.22215/cujs.v5i2.5320

Exploring the Experiences of Multiple Perspectives Within Equine-Assisted Programs Using Photovoice

2025· article· en· W4414402524 on OpenAlexaffabout
Brooke Bowditch, Vivian Lee

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsCarleton University
Fundersnot available
KeywordsPhotovoiceFacilitatorThematic analysisReflexivityRecreationFeelingQualitative researchParticipant observationNarrativeData collection

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the motivations and experiences of people who participated in various equine-assisted therapeutic programs. There is a need to broaden and explore the range of recreational services available to individuals with neurodevelopmental conditions and their families. The present study collaborated with TROtt, a therapeutic riding barn based in Ottawa, to collect data as a measure of their quality assurance. Participants of the current study included two instructors, one equine-assisted learning facilitator, two adult volunteers, one staff member, and one facilitator for an equine-assisted social group for young adults on the spectrum. The study used a qualitative method called Photovoice or photoelicitation, a non-invasive and participant forward way to capture participant perspectives. Participants took photos of various aspects of their equine-sessions including horses, barn equipment, and nature and then submitted those photos with a short accompanying narrative explaining the photo’s significance to their experience. Through a reflexive thematic coding analysis, results demonstrated that equine-based programs provided many benefits to participants including feelings of autonomy, opportunities to develop new skills, finding a sense of community, positive emotions, multisensory experiences, opportunities for non-verbal communication, and a calming environment. By moving towards a better understanding of motivations, preferences, and values that drive engagement in equine-based services, our work can allow for a more comprehensive knowledge of how to better structure and program recreational services to reach broader audiences.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.005
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
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 head0.158
GPT teacher head0.409
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueCarleton undergraduate journal of science.Same topicReflective Practices in EducationFrench-language works237,207