MétaCan
Menu
Back to cohort
Record W3008642921

Reflections on the provision of veterinary services to underserved regions: A case example using northern Manitoba, Canada.

2018· article· en· W3008642921 on OpenAlexaffabout
Caroline Boissonneault, Tasha Epp

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousDewormingMedicineVeterinary medicineGeographySocioeconomicsSociology
DOInot available

Abstract

fetched live from OpenAlex

Rural, remote, and Indigenous communities often contend with free-roaming dog populations, increasing the risk of aggressive dog encounters, particularly dog bites and fatal dog attacks. This qualitative survey gathered a range of perspectives to ascertain the current veterinary services available in rural, remote, and Indigenous communities of northern Manitoba, as well as needs, barriers to, and considerations for future veterinary care provision. Survey results indicated terminology such as "overpopulation" and "rescue" need to be carefully considered as they may have negative connotations for communities. While veterinary services such as vaccination and deworming are important for public health, most programs were focused on sterilization. There was consensus that conversations must begin with individual communities to determine what services are needed and how to fulfil those needs. Perceived barriers include the remoteness of communities, finances, and culturally different views of veterinary medicine. Recommendations for future delivery of services include increased frequency and funding of current models, while others focused on different methods of delivery; all of which will require further discussions within the veterinary community and with other stakeholders.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.178
GPT teacher head0.363
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2018
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicHuman-Animal Interaction StudiesFrench-language works237,207