Not So Perfectly Frank: Getting Clear on Organizational Candor
Bibliographic record
Abstract
Practitioners have shown a strong interest in increasing candid communication in the workplace. However, there are still few, if any, examples of organizations that can claim to have reached an ideal level of open communication with all relevant stakeholders. Both employees and leaders continue to hold back information in ways that hurt organizational functioning. In this paper, we aim to improve our understanding of candor by integrating theories from a number of relevant literatures (e.g., employee voice, secrecy, lying, impression management) that address the development of or lack of honest and open communication between people in organizations. We extend beyond the dominant approach that focuses exclusively on the informational benefits of candor, to include a consideration of both the positive and negative impact of open communication in the workplace. Our theorizing begins with the core idea that the interpersonal relationship between the sender and receiver of a candid message is of central importance since it is the immediate context within which the communication occurs. We suggest that organizational leaders may find that encouraging candor requires a greater respect for the influence of these relationships. We discuss the limitations of our discussion and suggest areas for future research.
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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 | 0.015 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| 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".