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Record W4327639831 · doi:10.1007/978-3-031-24910-5_11

Professions, Knowledge, and Workplace Change: The Case of Canadian Engineers

2023· book-chapter· en· W4327639831 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueKnowledge and space · 2023
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsFiduciaryPublic relationsTraining (meteorology)EngineeringPolitical scienceBusinessKnowledge managementEngineering ethicsComputer science

Abstract

fetched live from OpenAlex

Abstract In North America, training in engineering has long been balanced between formal university education and on-the-job training. Over the last few decades, however, Canadian engineering workplaces have changed. In the drive for efficiency and profit, firms are increasingly reluctant to invest in training. This paper’s author draws on interviews with 53 Ontario, Canada, engineers to explore how workplace change impacts professional skills, and to identify the implications for professional knowledge. From her findings, she concludes that engineers have fewer opportunities to learn on the job than in the past. Increasingly, many are asked to learn in their own time, or on an ad-hoc basis to complete pressing tasks. This encourages information gathering, rather than building deep knowledge. Moreover, knowledge benefiting employers is emphasized at the expense of knowledge benefiting society, with potential long-term implications for engineers’ fiduciary responsibilities.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.700
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.031
GPT teacher head0.235
Teacher spread0.204 · 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