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Record W4401654715 · doi:10.1002/cjce.25468

Perspectives on 40‐year careers—University of Calgary Chemical & Petroleum Engineering graduating class of 1983

2024· article· en· W4401654715 on OpenAlexaffvenueabout
Robert E. Wichert, Anil K. Mehrotra, Gregory S. Patience

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsPolytechnique MontréalUniversity of Calgary
Fundersnot available
KeywordsRecessionGovernment (linguistics)Petroleum industryPetroleumWork (physics)Class (philosophy)Engineering educationManagementEngineeringEconomicsChemistryEngineering management

Abstract

fetched live from OpenAlex

Abstract Only a few of the students who graduated from Chemical & Petroleum Engineering at the University of Calgary found jobs in 1983 because of a severe recession and the National Energy Program artifically deflating the oil price. Despite the slow start to their careers, the graduates have made substantial contributions to industry, government agencies, and academia. They worked on over 60 projects in more than 40 countries, many of which were valued in the billions of dollars (excluding projects in Canada). Because of the volatility in the petroleum industry, the graduates often moved from one company to another: 6 individuals worked for 10 or more companies, while only 2 spent their entire career at a single company. In 1981, we were told that the half‐life of an engineering career was 5 years, but while many did take up senior management positions and business roles, most remained very close to the engineering profession throughout their careers. Here, we summarize the career paths in broad terms, like how frequently graduates changed jobs, how much time they averaged in each company, and mention the role of education in their work. Of the 60 students who graduated in 1983, this perspective article excludes seven engineers who passed away prematurely, and another seven who could not be reached.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.832

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 integrity0.0000.001
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 routes3
Has abstractyes

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