Ethical Considerations in Research about Organizations: Compendium of Strategies
Bibliographic record
Abstract
This paper concerns ethical considerations when conducting research about the policies, procedures, practices, and culture of organizations and institutions rather than research with the humans owning, operating, employed at, volunteering for, benefiting from, or impacted by the organization. Ethical conventions for research with humans are well developed but less so for research about organizations. A pressing concern in the nascent literature is weighing protecting the public interest versus the organization’s interests when sensitive, controversial, or damning information about the latter emerges from the research. Given the absence of formally codified procedural ethics, organizational researchers are encouraged to constantly reexamine, debate, and address related ethical concerns. In that spirit, an inaugural compendium of ethical concerns and recommended strategies gleaned from the literature reviewed is shared, and a discussion of omissions from said literature is tendered to scaffold future conversations around this ethical aspect of organizational 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 | 0.347 | 0.245 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.013 | 0.096 |
| Scholarly communication | 0.034 | 0.029 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.032 | 0.046 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".