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Record W3031447871 · doi:10.1016/j.chbr.2020.100013

The meaning of the experience of being an online video game player

2020· article· en· W3031447871 on OpenAlexafffund
Kelly Arbeau, Cassandra Thorpe, Matthew Stinson, Benjamin Budlong, Jocelyn Wolff

Bibliographic record

VenueComputers in Human Behavior Reports · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversity of AlbertaTrinity Western UniversityWestern University
FundersUniversity of AlbertaTrinity Western University
KeywordsMeaning (existential)PsychologyVideo gameNarrativeExperiential learningSet (abstract data type)Social psychologyIdentity (music)Online videoVariety (cybernetics)MultimediaComputer scienceAestheticsPedagogy

Abstract

fetched live from OpenAlex

Online video games contain a variety of features that facilitate or encourage social interaction among game players. We explored the meaning of the experience of online game playing, seeking to uncover the personal meanings that game players ascribe to their online gaming experiences. Guided, semi-scripted personal interviews were conducted with 16 participants aged 17 to 34. A psychological-phenomenological analysis of participant narratives was conducted following procedures set out by Giorgi (2009). Four descriptive themes were identified: social rewards, experiential enhancement, growth and identity, and tension reduction. Participants described online gaming as an overwhelmingly positive, rewarding experience shaped by their social interactions with others in the game. We propose that as games offer more and more options for positive social interaction, concerns about detrimental effects of online video games may be attenuated.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.010
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0010.002
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 head0.060
GPT teacher head0.352
Teacher spread0.292 · 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

Citations58
Published2020
Admission routes2
Has abstractyes

Explore more

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