Positively Deviant: Identity Work Through B Corporation Certification
Bibliographic record
Abstract
Despite widespread and growing public interest in sustainability certifications, many social entrepreneurs have opted not to obtain such certification. Drawing on recent studies highlighting the salience of both gender and context in shaping differences among social enterprises, we develop an identity-based framework for explaining heterogeneity in the adoption of sustainability certification. We test our ideas using a sample of 1251 U.S. firms obtained from B Lab, the organization responsible for assessing Certified B Corporations. Our results show that woman-owned businesses are twice as likely to qualify for certification and more than three times as likely to certify. Moreover, this propensity to certify is amplified in contexts where sustainability norms are weak, mimetic pressure to obtain sustainability certification is low, and woman-owned businesses are less prevalent. These findings support our central theoretical argument that certification differences are due to actors' efforts to engage in identity work, strengthening their sense of self-coherence and distinctiveness by way of this authentication process. We conclude by highlighting our contributions to existing scholarship on social entrepreneurship, identity work, and certification adoption, as well as strategic implications for B Lab.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".