Fine‐tuning Livingstone and Adams' ethical principles for integrity in gambling research
Bibliographic record
Abstract
There is clearly a need for ethical principles to guide integrity in gambling research. Some fine-tuning on these principles and an iterative process for edit, review and sign-off has potential to rise above the cosy vested-interest industry–government research agenda that blames individuals for gambling-related harms and protects ‘business as usual’. Livingstone & Adams have put forward five principles for integrity in gambling research, aimed at countering the current inertia in progressive public interest research 1. This is a welcome initiative, which has been under discussion for some time. It is a start to settling on some principles. However, their first principle is more complicated than it looks. The funding for research has to come from somewhere, and independent national academic funding bodies have been slow to recognize the need for investment in progressive gambling research. Conducting research at arms-length from industry funding has been handled quite successfully by VicHealth, the independent public health research body in Victoria, Australia, funded from the tax on tobacco 2. Principle 1, therefore, needs to address industry direct funding of research, conflict of interest and industry dominance over research priorities, to avoid vetoing research where publicly derived funds, e.g. via taxation, are used for independently commissioned research. Livingstone has conducted independent research under such funding from the independent Gambling Research Panel, which was funded indirectly from gambling taxes 3, and the UK charity StoptheFOBTs campaign, which is funded by a retired international poker player 4. To enshrine independence, the first principle also needs the added stipulation: ‘or funded or conducted via any form of involvement of or partnership with the gambling industry or government’. Of relevance to all jurisdictions with licensed gambling, the internationally lauded Australian Productivity Commission inquiry recommended that a national independent research institute be established 5, 6. A new second principle could stipulate that research should be conducted by an independent statutory national institute which reports to Parliament. Independence would be driven by public interest governance and research priorities on consumer protection, prevention of harm and a veto on industry involvement. The third principle addresses the need to differentiate industry conferences and forums from credible independent research conferences. As Livingstone & Adams argue, academic attendance at industry conferences ends in compromise. This needs to strongly exempt any industry sponsorship or formal participation and could develop international conference accreditation. Conference accreditation could be conducted by an international board or committee elected by independent researchers who commit to independent research conferences, workshops and symposia. The fourth principle, requiring full funding source disclosure in journals and at conferences, highlights the need for stringent standards for both editors and contributors. Moreover, some of the leading researchers internationally, have conducted unpublished research funded for undisclosed amounts by the gambling industry, while at the same time presenting their other research as independent and free of industry influence 7. Disclosure of any life-time industry funding would overcome this hurdle. The fifth principle attempts to incorporate much-needed research access to gambling venues, products and internal industry working documents, such as industry-funded research reports and analysis. For tobacco, landmark US litigation resulted in the disclosure of covert tobacco industry research and corporate and political activity, resulting in greater transparency 8. Stronger wording would recognize that access for research must be part of the regulatory contract. Public interest principle-driven research has the potential to rise above the cosy research agenda that blames individuals for gambling-related harms and protects ‘business as usual’ gambling industry/government vested interests. In the future, the proposed website can bring together a consortium of ethical researchers to drive this agenda internationally. The author is a Chief Investigator in an Australian Research Council Linkage Grant investigating mechanisms of industry influence in the tobacco, alcohol and gambling industries. She has conducted many international independent reviews, including for Canadian governments. She has received no funding directly or indirectly from gambling or alcohol industry sources for any purpose.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".