Bibliographic record
Abstract
Since the mid-2010s, Certified B Corporations and Benefit Corporations, both commonly referred to as B Corps, have emerged as a global phenomenon. These organizational forms are adopted by for-profit businesses. Whereas Certified B Corporations have been accredited for their environmental, social, and governance (ESG) practices, Benefit Corporations are a new legal form, currently available in forty states, the District of Columbia, and Puerto Rico in the United States as well as in British Columbia (Canada), Colombia, Ecuador, France, Italy, and Peru. These innovations were promulgated by B Lab, a US-based nonprofit organization. Founded in 2006 in the suburbs of Philadelphia, Pennsylvania, B Lab has sought to institutionalize business as a force for good. To date, certification is available to any business worldwide, and approximately eight thousand companies in ninety-three countries were certified as of January 2024. Prominent Certified B Corporations include Ben & Jerry’s, Coursera, Danone North America, Patagonia, and TOMS. Examples of Benefit Corporations include Allbirds, data.world, Kickstarter, and Plum Organics. Overall, the B Corp movement’s radical aspiration to redefine business has garnered substantial attention from policymakers, media, businesses, nongovernmental organizations (NGOs), and academics. This article provides an overview of burgeoning scholarly work—ranging from general references and cutting-edge theoretical work to empirical research evidence and key pedagogical resources. A core focus is on enumerating the variety of theoretical perspectives and central research themes in extant work, including interdisciplinary publications. We close by discussing exemplary teaching materials and introducing other resources, such as the B Academics research community, a chronology of key thematic research events, and data sets available to researchers. Overall, the bibliography, first published in 2021, serves as a living repository of B Corp scholarship, past and emerging, for a broad range of veteran and nascent B Corp academics across multiple disciplines.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".