A Submission on Greenwashing to the Senate Environment and Communications References Committee
Bibliographic record
Abstract
The Australian Senate has established ‘an inquiry into greenwashing, particularly claims made by companies, the impact of these claims on consumers, regulatory examples, advertising standards, and legislative options to protect consumers.’ The terms of reference observe that the inquiry on greenwashing will focus on (a) the environmental and sustainability claims made by companies in industries including energy, vehicles, household products and appliances, food and drink packaging, cosmetics, clothing and footwear; (b) the impact of misleading environmental and sustainability claims on consumers; (c) domestic and international examples of regulating companies' environmental and sustainability claims; (d) advertising standards in relation to environmental and sustainability claims; (e) legislative options to protect consumers from green washing in Australia; and (f) any other related matters. The Australian Senate Environment and Communications Reference Committee is investigating the topic of greenwashing – with a view to publishing a report by December 2023. The researcher has longstanding interest in greenwashing – as part of a larger body of work looking at intellectual property, the environment, and climate change. The author has also taken a keen interest in the adjoining field of intellectual property and sustainable development – with a focus on the right to repair. The researcher has a broader interest in how international trade law deals with questions of sustainability as well. The author is interested in how regulatory systems deal with fakes and frauds. This submission is based upon research of the author over the past decade in respect of greenwashing – looking at misleading and deceptive representations about the environment, sustainability, and climate change in a variety of fields. This work traverses a variety of legal disciplines – including advertising regulation, consumer law, competition policy, corporations law, environmental and climate litigation, intellectual property law, Internet regulation, and freedom of speech (in terms of constitutional law and human rights law). This research is also comparative – and has looked at the position of Australia, alongside that of the United States, Canada, the United Kingdom, the European Union, and Nordic states such as Norway, Sweden, Finland, and Denmark. This submission makes a number of recommendations and suggestions as to how to modernise Australia’s legal regimes, so that they are better equipped to deal with the risks, problems and challenges of greenwashing. It also provides advice in respect of legal enforcement by key regulators in respect of the problem of greenwashing. The submission highlights the need for stronger international frameworks to better deal with the risks of greenwashing.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.029 | 0.016 |
| Insufficient payload (model declined to judge) | 0.108 | 0.068 |
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".