Industrial Engineers on their Current Practice: Implications for the Integration of Social and Technical Sub-Systems in Work System Design
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.
Bibliographic record
Abstract
<p>Sub-optimal work system design results in ill-effects for individuals, businesses, and society. By improving the integration of social and technical systems in design by industrial engineers, work system outcomes could be improved. Semi-structured interviews were conducted with 19 Canadian industrial engineers. Data was transcribed, coded, and analyzed using an iterative, inductive process. Results showed that industrial engineering practice is diverse and is influenced by macro-, meso-, and micro-level ecological factors. Stakeholder awareness of industrial engineering, management support and understanding, role clarity, organizational structure, and relationships between industrial engineers and management, system users, and ergonomists all influenced the effectiveness of industrial engineers. It was concluded that a systemic approach to changing the work system design process is most likely to be successful in establishing consistent, long-term improvement of work system outcomes and application of ergonomics. Further investigation of work system design practices from the perspective of management and system users is recommended. </p>
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it