Balancing Interests in the Search for Occupational Legitimacy: The <scp>HR</scp> Professionalization Project in Canada
Bibliographic record
Abstract
Despite broad debates surrounding how the human resource management occupation can increase its legitimacy, researchers have yet to examine the collective steps HR practitioners are taking in this regard and the extent to which they have been successful. We conduct a case study of the HR professionalization project in Canada via multisource qualitative and quantitative data, which we analyze using a unique integration of the trait and control models from the sociology of professions, as well as isomorphism from institutional theory. Viewed through the lens of these frameworks, we find that HR practitioners are attempting to emulate traits that define traditional notions of professions, and are aspiring to transcendent values associated with balancing the sometimes conflicting interests of employers and employees. Objective data from external stakeholders and institutions show that these collective strategies have been somewhat successful in garnering greater legitimacy thus far, particularly when comparisons are made with the HR professional project in the United States. We highlight numerous implications for future research and practice surrounding the legitimacy of the HR profession. © 2014 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.033 | 0.017 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".