What is special about gambling? A comparison of public discourse on Finnish state monopolies in rail traffic, gambling, and alcohol
Bibliographic record
Abstract
Finland has one of the last fully monopolistic gambling sectors in Europe. Unlike in most Western European countries, the monopoly is also consolidated and enjoys a wide support as opposed to license-based competition. This paper analyses whether this preference for monopoly provision is due to the particularities of the Finnish society or rather to those of the Finnish gambling sector. We do this by comparing public discourses in media texts (N=143) from 2014 to 2017 regarding monopolies operating in alcohol retail, rail traffic and gambling sectors. The results show that gambling appears to be special even in the Finnish national context. While the Finnish alcohol retail and railroad traffic markets have been liberalised during the study period, the gambling monopoly has been concurrently strengthened despite similar political and international pressures towards dismantling. The discussion suggests that the differing outcomes reflect the varying positions of monopolies, their stakeholders and the justifications put forward. Intertwined stakeholder interests in the gambling sector appear to amplify consensus politics and set gambling apart from the other cases.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| 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".