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Record W2734811218

Hybrid Moments: Using Ludonarrative Dissonance for Political Critique

2016· article· en· W2734811218 on OpenAlexaff
David Thomas Murphy

Bibliographic record

VenueLoading... · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCognitive dissonanceCriticismEpistemologySociologyIdeologyNarrativePoliticsArgument (complex analysis)Media studiesPsychologySocial psychologyPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Game criticism, from a historic perspective, traditionally follows an objectively oriented approach. But in recent years a new tide of personally oriented writing has been emerging in online spaces alongside more traditional publishing models. Game scholars, motivated by the large audiences that online pieces can attract, are not only participating in this scene, but also promoting it as the primary source for progressive criticism. While such pronouncements are correct in many cases, the video game blogosphere is also not immune from the cultural privileging of “gamers,” a problem that has been identified by feminist and critical theoretical approaches to the study of gaming culture (Kubic, 2012; Shaw, 2012, 2013; Consalvo, 2012; Vanderhoef, 2013). To better illustrate the aforementioned point, this article will both examine and comment on the recent online debate that arose over use of the term “ludonarrative dissonance” (Hawking, 2007), a critical concept referring to formal, thematic, and ideological disconnects between ludic and narrative meaning. It will begin by contextualizing the ludonarrative dissonance debate within a brief history of methodological approaches to game criticism. The focus will then shift to discussion of the term itself, and how it provides a useful critical framing by treating simulation and representation as interacting components with the capacity to coincide and contradict. Ludonarrative dissonance, understood as a formal problem, has entered the vocabulary of many critics, but the term is also dismissed for a variety of reasons, including the insistence that experienced gamers learn to ignore inconsistencies between story and design (Yang, 2013). Rejecting this argument, this article concludes by drawing upon assemblage approaches to play (Taylor, 2009; Pearce & Artemesia, 2009; Parikka, 2010) to argue that ludonarrative dissonance does exist and that the concept provides a useful starting point for examining the political tensions implicit in many games—tensions that are often acknowledged but frequently downplayed in existing formal and political approaches to criticism. The analysis of ludonarrative dissonance, from this perspective, not only pushes criticism beyond the aesthetic appraisals gamers, it can also provide insight into the nuances of games that reinforce problematic political discourses while simultaneously simulating potential systematic alternatives to neoliberal corporate capitalism.

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)0.030
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0080.064
Scholarly communication0.0150.014
Open science0.0040.011
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.036
GPT teacher head0.357
Teacher spread0.321 · 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 designTheoretical or conceptual
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

Citations1
Published2016
Admission routes1
Has abstractyes

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