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Record W3033502604 · doi:10.3138/jvme.2019-0087

Collaboration Spanning Two Continents: An Online Master’s Degree in Tropical Animal Health

2020· article· en· W3033502604 on OpenAlexvenueno aff
Mieke Stevens, Darshana Morar-Leather, Chiara Trevisan, El-Marie Mostert, Marinda C. Oosthuizen

Bibliographic record

VenueJournal of Veterinary Medical Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsJoint (building)Work (physics)CurriculumMedical educationDegree programDistance educationQuality assuranceMedicinePsychologyEngineeringPedagogy

Abstract

fetched live from OpenAlex

A joint international program in Tropical Animal Health was launched in 2016 by the Institute of Tropical Medicine, Antwerp, Belgium, and the Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria. This program is flexible in time, place, and curriculum, allowing part-time students to apply the program's learning outcomes directly in their daily work environment. This article focuses on the major challenges and issues related to developing an international joint program in general and how these challenges were addressed. Challenges such as incompatibility of admission procedures, merging academic calendars, and quality assurance mechanisms were mitigated partly by the type of collaboration and partly by using a joint e-learning platform. The e-learning format proved to be a solution for particular challenges such as mobility issues, joint development of course material, and administrative processes. Furthermore, we present the results of a survey on the experiences of graduates and facilitators in this unique joint, web-based program.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.243
GPT teacher head0.402
Teacher spread0.159 · 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 designOther design
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

Citations3
Published2020
Admission routes1
Has abstractyes

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