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Record W3011169823

Towards an Enriched Understanding of People Who Experience Problem Video Gaming

2018· dissertation· en· W3011169823 on OpenAlexfundaboutno aff
Jing Shi

Bibliographic record

VenueTSpace · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMultimediaComputer science
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Video game addiction, also known as problem video gaming, is making headlines across the globe. Yet, our understanding of this relatively new phenomenon is limited. The purpose of this thesis is to develop an enriched understanding of people who experience problem video gaming. Methods: Two studies and a synthesis paper were completed. 1) A quantitative secondary analysis of survey data to determine the prevalence and correlates to problem video gaming. 2) A qualitative study using interviews and activity logs to understand the lives of people who experience problem video gaming from their own perspectives. 3) A synthesis of the two studies to facilitate a new discourse that broadens our understanding of problem video gaming. Results: Descriptive statistics found that 11.6% of youth experience problem video gaming. Logistic regressions revealed that the strongest predictors of problem video gaming were: being male, scoring lower in mental health status, playing more hours per day, being a problem gambler, receiving less parental monitoring, scoring lower in school subjective social status, not living in the East region of Ontario, and not working outside of the home. People who experienced problem video gaming described playing video games as a meaningful and purposeful activity. A model that explains the push and pull influences on the amount of gaming is described. The synthesis of these results demonstrated that problem gaming behaviours are influenced by issues arising not only in the individual, but also in the interpersonal and environmental circumstances. Significance of Findings: This thesis fosters new insights into the complexity of problem video gaming by explicating the interactions between the individuals who experience this, their interpersonal influences, and their environments. Consequently, the findings point to the importance of interpersonal and/or environmental issues which may have resulted in a misrepresentation of some gamers as being “addicted”.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.013
Scholarly communication0.0100.015
Open science0.0020.008
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.382
Teacher spread0.332 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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