Sustainability in entrepreneurship: A tale of two logics
Bibliographic record
Abstract
Given the uncertainty surrounding the role and meaning of sustainability in business practice, it is important to explore the legitimacy drivers that newcomers (entrepreneurs) to a field derive from balancing sustainability and profitability. Drawing on the institutional logics literature and Bourdieu’s notion of habitus, this article theorizes how the characteristics of the field, as well as entrepreneur characteristics and actions, influence the legitimacy derived from adhering to the field-prescribed balance between sustainability and profitability. First, regarding the role of field-level factors, we discuss how the impact of field-imposed expectations on entrepreneur legitimacy may be amplified for dominant and mature fields. Second, regarding the role of micro-level factors, we highlight that whilst previous experience of the field-prescribed balance between sustainability and profitability may amplify the impact of field-imposed expectations on legitimacy, strategic actions can suppress this impact.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.069 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".