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Record W2925761282 · doi:10.7202/1058317ar

Not Yet Game Over: A Reappraisal of Video Game Addiction

2019· article· en· W2925761282 on OpenAlex
Jiow Hee Jhee, Qin Ting Lye, Kenneth Woo

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

VenueLoading · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsVideo gameAddictionPsychological interventionThe InternetPsychologyFocus (optics)Online videoComputer scienceMultimediaNeurosciencePsychiatryWorld Wide Web

Abstract

fetched live from OpenAlex

The rapid expansion of video gaming in an internet-using society has brought on a renewed focus on the phenomenon of video game addiction. Despite this focus, there remains a crucial absence of consensus over the diagnostic criteria of video game addiction. Currently both psychological and behavioral interventions regard screen time as an indicator of video game addiction. However, these interventions are challenged by substantial literature that increasingly regard time to not be a predictor of addiction. To build onto the work that has been done, this paper argues that time is an inadequate criterion in which to ascertain video game addiction, proposing that a physiological-based criteria be used in conjunction with contextualized understandings of video game dynamics to approach video game addiction. This realignment is all the more pressing as video games begin a transition from a leisure activity to its current orientation as a viable career option.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.314
Teacher spread0.299 · 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