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Record W4398218461 · doi:10.3389/feduc.2024.1396377

Student perception of sustainability in industry: a case study in an undergraduate petroleum processing course

2024· article· en· W4398218461 on OpenAlexaff
Sourojeet Chakraborty, Sadafnaz Kashi Kalhori, Yris González, Jorge Mendoza, Daniela Galatro

Bibliographic record

VenueFrontiers in Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCourse (navigation)SustainabilityPerceptionPetroleumPetroleum explorationEngineering managementComputer scienceEngineeringPsychologyGeology

Abstract

fetched live from OpenAlex

Research demonstrates a predominantly negative public perception of the oil and gas (O&G) industry, regardless of initiatives created to minimize the environmental impact. This might be attributed to a lack of open communication and debate spaces where these initiatives are learned and discussed. To test our hypotheses within a university setting, a major revamp of the course “Petroleum Processing” in our university was implemented, where sustainability concepts and open discussion were assimilated into the lecture content. Pre- and post-surveys were conducted to assess students’ perceptions regarding sustainability in the O&G industry before and after the course. Perceptions remained unchanged following course delivery. However, students believe they are more informed about the sustainability approaches implemented.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.409
Teacher spread0.393 · 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 designObservational
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

Citations9
Published2024
Admission routes1
Has abstractyes

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