Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gambling advertising’s use of celebrities, humor, and representations of happy people who Win Big, in narratives told in brash colored, high-pitched ads, are argued to increase the risk for gambling problems, or worse, addiction. Online casino ads have been subject to particular legislative attention partly for these reasons, as well as for being increasingly targeted to women who, by some, are judged to be especially vulnerable to such marketing. This paper presents a context-attentive, multimodal discourse analysis of a Swedish online casino brand’s advertising videos from 2014-2022. The study illustrates how general statements regarding risk in relation to (online casino) gambling ads’ content dramatically reduces their potential cultural significance to audiences. It is argued that one should, to a greater extent, treat these adverts as complex and socio-culturally rooted texts whose content may not so easily be written off as simply “risky,” to women or otherwise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 it