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Record W1936428780 · doi:10.24908/pceea.v0i0.5886

Sustainability Entrepreneurship in Engineering

2015· article· en· W1936428780 on OpenAlexaffvenue
Amy Hsiao

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Sustainability
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSustainabilityEntrepreneurshipProduct-service systemSustainability organizationsSocial sustainabilityBusinessWork (physics)Sustainability scienceProduct (mathematics)Engineering ethicsEngineeringKnowledge managementBusiness modelMarketingMechanical engineeringComputer scienceEcology

Abstract

fetched live from OpenAlex

Sustainability entrepreneurship is the use of innovative enterprise in a strategic manner to address a sustainability-related issue. By its operation, the process of sustainability entrepreneurship adds to the improvement of social, economic, and environmental concerns related to human quality of life. This work proposes that the distinction of sustainability entrepreneurship is having the business activity a characteristic of the innovation and making engineering or technology a critical component of the business solution. This work discusses how sustainability entrepreneurship can be introduced in undergraduate and graduate engineering curriculum, specifically through a materials science laboratory, engineering entrepreneurship, and engineering management experiences. Examples in this work demonstrate that sustainability entrepreneurship is a progression that begins with an understanding of the technical issues of sustainability as an engineering student, moves to the motivation, drive and identification of an opportunity that creates of a product or service valuable to an identified market, and finally creates a business that adds to the sustainability of life-supporting systems in the process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.014
Scholarly communication0.0070.004
Open science0.0000.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.259
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2015
Admission routes2
Has abstractyes

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