“Come play with us!” A grassroots research agenda for accounting and the circular economy
Bibliographic record
Abstract
The dominant global capitalist economic model harms ecosystems and humxn populations. In attempting to reduce these harms, its linear foundational elements characterised by rapid production, mass consumption, and ineffective disposal necessitate a shift to more circular approaches. Embracing circularity is complex and requires several elements in addition to shifting business approaches such as redefining value, discarding traditional competitive practices in favour of collaboration, and developing appropriate tools for analysis. Given both its ubiquitous role in business and its ability to facilitate change, it appears a natural extension for accounting to serve an essential function in the circular transition. With this in mind, this editorial serves a twofold purpose. It first introduces the present special issue on “Accounting for the Circular Economy” and contextualises the circular economy concept. Secondly, it relies on insights from interviews with circular economy experts to propose a grassroots agenda for accounting within the circular economy context. Given the pressing need to address environmental and social challenges, we hope this editorial and the articles published in the special issue will spark further research and practical transformations toward a more regenerative and just economic and social system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.023 | 0.024 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".