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Record W4415225069 · doi:10.15173/ijsap.v9i2.6646

A SaP engagement in experiential learning daily debriefs

2025· article· en· W4415225069 on OpenAlexaffvenue
Anton McLean, Rebecca Wilson-Mah, Ching Hei Cheung, Emma Cockram, Malahat Gurbanalieva, Weike Huang, Xinyuan Hu

Bibliographic record

VenueInternational Journal for Students as Partners · 2025
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsRoyal University HospitalRoyal Roads University
Fundersnot available
KeywordsMindsetExperiential learningTransformative learningDebriefingTourismExperiential educationGeneral partnershipInformal learningValue (mathematics)

Abstract

fetched live from OpenAlex

This co-authored case study shares student perspectives on the relationship between daily debriefs and their experiential learning during a 5-day regenerative tourism field study. The pedagogical goal of this partnership was to offer five MA in Tourism Management students the opportunity to develop knowledge, skills, attributes and appreciation of a regenerative tourism experience. The findings of this case study illustrate the value of experiencing an embodied and holistic tour that was regenerative in design. Furthermore, the daily debrief activity was used as one example of how a holistic regenerative tour informed a transformative mindset for all.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0030.001
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 head0.044
GPT teacher head0.504
Teacher spread0.460 · 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 designNot applicable
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

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