Bibliographic record
Abstract
The aims of this paper are twofold: first, to demonstrate the importance and relevance of interpretive political analysis to gambling research and second, to analyze from the aforementioned perspective why politicians in Finland talk about gambling harm and gambling revenue the way they do. The speeches of the representatives in the Parliament of Finland during debates on gambling policy are analysed as political action. The analysis has three levels. The first focuses on the themes of the speeches. The results show that there are four distinct thematic dimensions in the speeches: gambling harm, revenue, regulatory system, and regulation. The second level of analysis establishes the contexts where certain themes typically occur. Typically, revenue is discussed in the context of the economic aspect of gambling while gambling harm is discussed in the context of the justification of the regulatory system. The third level of analysis explains why the themes occur in the contexts they do. The representatives´ acceptance of the self-evidence of the regulatory system forecloses any possibility of getting support for major changes to the system. This explains why the official policy aims of reducing and preventing gambling harm have not been realized. It is concluded that the approach introduced can help to understand the political aspects of gambling.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".