Conflicting and Complementing Logics: Examining Sustainability Practices Across Economies
Bibliographic record
Abstract
The role institutional environments play in sustainability practices across countries is well documented in the international business literature. However, how multiple and occasionally conflicting institutional logics shape sustainability practices at the individual-level is underexplored, especially across countries. To enhance our understanding of this process, we investigate how individuals in two high-hazard organizations in the energy sectors in the Republic of Serbia and Canada practice sustainability. Our findings illustrate that in both contexts, individuals “pull down” structural elements of high-hazard logics into their daily sustainability practice, thereby relating their practices to the well-being of others as well as aligning them to their salient identities. However, our findings also illustrate how multiple, often conflicting, logics interact to shape this process distinctively across two countries. In Serbia, individuals pull-down and combine elements of high-hazard and legacy state logics to construct community logic and align their practice to it. In Canada, individuals do so to construct professional logics and align their practice to it. Based on our comparative case analysis of a developed economy and an economy in transition, we create a general model, as well country-specific models, depicting how individuals navigate multiple institutional logics to engage in sustainability practices.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| 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".