MétaCan
Menu
Back to cohort
Record W2374421917 · doi:10.4101/jvwr.v2i1.374

Canadian Border Simulation at Loyalist College

2009· article· en· W2374421917 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Virtual Worlds Research · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methodologies in Social Sciences
Canadian institutionsLoyalist College
Fundersnot available
KeywordsGRASPProcess (computing)Class (philosophy)Mathematics educationComputer scienceBorder SecurityPsychologyMedical educationPolitical scienceArtificial intelligenceLawSoftware engineeringMedicine

Abstract

fetched live from OpenAlex

The aim of this paper is to describe the process and results of a Canadian border simulation run in Second Life for students at Loyalist College. Recent security restrictions at the Canadian border limit access for college students to serve their placement at the actual border, thus eliminating the possibility of first hand experience. Additionally, in class role-plays designed to practice border interview skills were not adequate to instill the interview process. Using Second Life to simulate the border environment and procedures allows students access to a simulated real life environment, and provides them with the sufficient real world practice they require to grasp and retain essential interview skills. The results of this learning experience translated into greater levels of confidence and significantly improved grades.

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)0.029
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.216
GPT teacher head0.562
Teacher spread0.347 · 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