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Record W4405739772 · doi:10.1089/glr2.2024.0029

Loyalty Rewards for Microtransactions on Video Games: Is This a Type of Gambling?

2024· article· en· W4405739772 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGaming Law Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsCentre for Addiction and Mental Health
FundersOntario Ministry of Health and Long-Term Care
KeywordsLoyaltyPsychologyAdvertisingBusinessMarketing

Abstract

fetched live from OpenAlex

My goal in this brief commentary is to describe a new type of game feature where people who play video games can earn reward points that can then be cashed out for gift cards or for cash in some countries. In-game purchases are not required to earn reward points, but people who spend real money on these games will earn more reward points. In my opinion, this scheme crosses the line into a form of indirect gambling. I use the term “indirect” because in many cases, the rewards are paid out from a different software application than the game itself, and the link between the money spent and the reward earned is indirect. The gambling law community needs to be aware of this scheme and determine if this constitutes gambling.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.092
GPT teacher head0.404
Teacher spread0.313 · 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