Honour, culture & valuing change : research on local culture shift
Bibliographic record
Abstract
Assertions that organizational change initiatives experience high rates of failure suggests knowledge about how culture shifts is incomplete. Framed in the context of Operation HONOUR, the Canadian Armed Forces’ effort to eradicate inappropriate sexual behaviours, this overview summarizes an interdisciplinary action research project which explores how culture shifts during a deliberate workplace change initiative. Employing a six-step Competing Values Framework process and a mixed-model design, the dissertational research project’s methods include a bespoke differential approach to unpacking quantitative data which is presented as valuing. This approach includes administration of the Organizational Culture Assessment Instrument (OCAI © 2006, Kim Cameron), open and axial coding of participant working group materials, and email exit interviews. Building on theory incorporated from multiple branches of the academe, this exploratory research uses the lens of culture as something people do, as an enacted phenomenon, to arrive at several insights. Notably, while the imperative to enhance the capacity of workplace members to lead their own workplace culture shift remains important, the role leaders play in championing culture shift is reinforced. Several themes linked to what “good” looks like for a just and inclusive workplace emerge, along with dimensions usable for qualifying success and detractors that can undermine a culture shift initiative. The three parts of the dissertational portfolio are summarized: two manuscripts and a seminar aimed at enhancing practitioners’ and scholars’ capacity to lead, or be an ally to, shifting culture in the workplace. The main contributions of this research are the development of the valuing approach to measuring culture shift, the emergence of themes and insights useful to researchers and practitioners, demonstration of mixed-methods’ utility, and the addition of knowledge to a limited body of applied research that frames workplace culture as enacted.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".