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Record W4400805020 · doi:10.4309/zwuh8188

Non-mathematical dimensions of randomness: Implications for problem gambling

2024· article· en· W4400805020 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Gambling Issues · 2024
Typearticle
Languageen
FieldComputer Science
TopicComputability, Logic, AI Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsRandomnessPsychologyHumanitiesMathematicsStatisticsPhilosophy

Abstract

fetched live from OpenAlex

As the demarcating lines between video gaming and gambling are increasingly blurred due to the embedding of so called "gambling-like" elements as loot boxes and prize wheels in video games, scholarly attention for this phenomenon is on the rise. Yet this strong attention comes with a downside: terminological dispersion. Indeed, the number of terms used to describe the emerging video game features that resemble gambling rapidly grows, and frameworks for naming diversify. This hinders a clear conceptualisation and solid scientific research findings, hampering the drafting of societally relevant recommendations for self-regulation of the industry and policy-making. Our study therefore maps the terminology used by experts from different disciplines studying the convergence between video gaming and gambling in the videogame ecology. It does so through a) an in-depth literature review searching for labels and b) a survey conducted among researchers to gauge for their used and preferred terms to describe the phenomena under study. Our findings point towards an effective circulation of the terms among academic experts, but without inter-expert consensus on their use, nor intra-expert terminological consistency. Some trends are identifiable: the use of terms placing phenomena on a continuum between gaming and gambling; the salient use of the term loot box, albeit not in a catch-all sense, and the attention for the presence of real money transactions. The terminological choices of experts seem to be oriented by distinguishable features: the visual outlook of the games, visual and textual references to gambling, the presence of opaque reward containers, and the visibility of in-game currencies and marketplaces. Finally, we sketch some recommendations for a terminology suited to interdisciplinary research and communication with non-academic stakeholders: treating the concept of simulation with caution, using loot box in its restrictive sense, being aware of the false feeling of understanding related to the gaming-gambling continuum, recurring to paraphrases to discuss the involvement of real-world currencies, and favouring explicitness.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.487
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.096
GPT teacher head0.386
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it