Bibliographic record
Abstract
This article makes a novel argument that governance of corporate environmental activities should recognize that the business corporation is an aesthetic phenomenon, including the environmental practices and communications undertaken in the name of “corporate social responsibility” [CSR]. Corporate identities and CSR practices are aesthetically projected through logos, trademarks, websites, the presentation of products and services, stylish offices, company uniforms, and other aesthetic artefacts. This corporate “branding” dovetails with the broader aestheticization of our pervasive media and consumer culture. Aesthetics has particular salience in CSR for influencing, and sometimes misleading, public opinion about corporate environmental performance. Consequently, in disciplining unscrupulous corporate behaviour, governance methods must be more responsive to such aesthetic characteristics. The green illusions of business communications create difficulties for regulation, which is better suited to disciplining discrete misleading statements about retailed products or trademarks rather than tackling the broader aesthetic character of business and the marketplace. The article suggests that non-state actors who are more sensitive to aesthetics can help to fill some of this governance void. The “counter-aesthetic” strategies of social and environmental activist groups can inject a subversive narrative that can help to unmask these green illusions. Although the history of such tactics suggests they probably have only a modest effect in challenging corporate deception, the law can assist by protecting public spaces from corporate marketing and sponsorship.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.058 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| 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".