Thwarted belongingness and empathy's relation with organizational culture change
Bibliographic record
Abstract
Introduction: In response to several high-profile cases of senior leaders in the Canadian Armed Forces (CAF) being accused of various forms of sexual and professional misconduct, the organization has committed to culture change. Drawing on the group engagement model and empirical evidence, we propose that CAF members' experience of thwarted belongingness reduces their capacity to show empathy, which in turn affects their support for culture change. Method: Participants were 139 Naval and Officer Cadets from the Royal Military College of Canada who were predominantly male (61%), between 18 and 21 years old (80%), and not members of a visible minority group (68%). Data was collected via an online self-report survey assessing thwarted belongingness, empathy, and attitudes toward culture change. Results: Whether participants experienced thwarted belongingness was not directly related to their level of support for culture change. Individuals' thwarted belongingness was indirectly and negatively associated with support for culture change, through its impact on empathy. Discussion: Taken together, the results demonstrate that cadets' experience of belongingness contributed to their level of empathy, which together predicted their support for culture change initiatives. Efforts to change the culture of the CAF may need to consider improving members' levels of belongingness and, by extension, their levels of empathy. Implications for inclusion efforts are discussed.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".