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Co-Op Education with a Sustainability Lens: A Case Study from University of Waterloo

2024· article· en· W4400410389 on OpenAlexaff
Shabnam Surjitsingh Ivković, Christine Moresoli, Norah McRae

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSustainabilityLens (geology)Computer scienceMathematics educationEngineeringPsychologyPetroleum engineering

Abstract

fetched live from OpenAlex

The University of Waterloo is world renowned for its co-operative education program. This type of education model lends itself greatly to excellent employability and career success outcomes across all faculties. The Faculty of Engineering is the seminal faculty at the university, and has mandatory co-op built into its DNA. The multiple experience model has resulted in high employability and career readiness outcomes. As a deeper quality aspect of the co-op model, bearing in mind the critical need to graduate students who can advance sustainability in their careers, specific programming has been put in place to develop this change agent mentality and pathways that has shown excellent outcomes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.999

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 communication0.0000.000
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 head0.048
GPT teacher head0.400
Teacher spread0.352 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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