Ambiguity and Abjection: Residents’ Reactions to a New Urban Casino
Bibliographic record
Abstract
While the social and economic costs and benefits of new gambling locations have been studied extensively, less is known about how new venues are experienced in view of city residents’ spatial and sociocultural identities. This study examines residents’ opinions and expectations on a new small-scale casino in the City of Tampere, Finland, as a case of new gambling opportunities in an urban setting. Nine focus group interviews were conducted with 43 Tampere residents three years prior to the scheduled casino opening. The study points out ways in which the residents struggled conceptually with the casino project. When speaking about it, participants drew on an imagery of popular culture, drawing a sharp line between casino gambling and the everyday convenience gambling so omnipresent in Finnish society. As residents of a historical industrial urban region, the participants positioned themselves as critical towards the municipality’s aims to brand the venue in a larger experience economy entity. By drawing on the concepts of city image and city identity, the study is able to demonstrate that the cultural geographical intrusion of new physical gambling spaces can appear as harmful to the city character. In the studied case, this is likely to hamper the City of Tampere’s chances to prevail on the very same experience market, of which the new casino is part.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".