Professional employees and professional managers: conflicting logics, hybridity, and restratification
Bibliographic record
Abstract
Abstract A plethora of studies have documented the changing nature of professional work and the organizations in which it takes place. Among the most documented trends are the emergence of managerial–professional hybrid workers and professional (re)stratification. Although the links between these two trends have been noted, their interconnections have not been fully explored. This article analyzes data from a mixed-methods study of professional engineers in Ontario, Canada, to explore the extent to which they experience conflicting logics, hybridity, resistance, and restratification. Findings indicate that many engineers could be classified as hybrid, as they see managerial roles as an extension of engineering. At the same time, many others see managers as oppositional to engineers, with different priorities. On the whole, there is evidence of restratification as the work experiences, professional attitudes, and responses to conflicting logics (hybridity or resistance) vary between managers and employees. This restratification has the potential to undermine professional unity.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".