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Record W4391603150 · doi:10.18260/1-2--43932

Landscape Review of Entrepreneurship Education in Canada and the Presence of Systems Thinking

2024· article· en· W4391603150 on OpenAlexaffabout
Amin Azad, Emily Moore

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEntrepreneurshipCurriculumRecessionSystems thinkingEntrepreneurship educationKey (lock)BusinessKnowledge managementEngineeringMarketingPolitical scienceEngineering ethicsEconomic growthComputer scienceEconomicsFinance

Abstract

fetched live from OpenAlex

Entrepreneurial activities have been driving forces of economies worldwide, bringing innovation and change to societies and pulling countries out of recessions. Increasingly, technology-driven innovation and entrepreneurship have become the key competitive advantages for a region or nation. There has been a push for universities to produce more entrepreneurs that can handle the challenges of today's world, and many engineering programs have begun to incorporate entrepreneurial education. Additionally, there has been an increased emphasis on systems thinking as an important capability for engineers as they seek to address complex challenges. This paper describes a scan of program offerings at Canadian post-secondary schools that address the topics of Entrepreneurship and Innovation and looks for evidence of Systems Thinking Teaching within the courses and curriculum.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.723
Threshold uncertainty score0.982

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 head0.004
GPT teacher head0.195
Teacher spread0.190 · 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 designSimulation or modeling
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 routes2
Has abstractyes

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