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Record W4414429763 · doi:10.1139/cjas-2025-0008

The face of the Canadian riding lesson industry—common management practices and industry opinions

2025· article· en· W4414429763 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Animal Science · 2025
Typearticle
Languageen
FieldMaterials Science
TopicMetallurgy and Material Science
Canadian institutionsUniversity of Guelph
FundersOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsWelfareThematic analysisDemographicsAnimal welfareQualitative propertyQualitative researchLesson study

Abstract

fetched live from OpenAlex

Riding lesson horses have generally poorer welfare than other types of horses. A survey was distributed to operators of Canadian riding lesson facilities to identify management trends that may influence the welfare of lesson horses, as well as to understand the demographics of the Canadian lesson herd and the people responsible for their care. The survey received 154 responses representing 13.2% ( n = 1550) of the total estimated Canadian lesson herd. Pearson χ 2 tests determined relationships among quantitative responses and thematic content analysis analyzed qualitative responses. Responses suggested that Canadian lesson horses largely receive species-appropriate care with daily access to group turnout and regular attention from veterinarians and farriers. A high level of concern for the health and comfort of lesson horses was demonstrated through use of complementary and alternative veterinary medicine, dietary supplements, joint injections, and/or ulcer and pain-management medications. Qualitative responses highlighted financial challenges and client expectations as significant obstacles to ensuring the welfare of lesson horses. This increased understanding of the landscape of the Canadian riding lesson industry provides new avenues for further research, suggesting that the reportedly poor welfare of lesson horses may not be related to management but other factors unique to the life of lesson horses.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.045
GPT teacher head0.316
Teacher spread0.271 · 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