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Record W2185685865 · doi:10.26503/dl.v2011i1.527

“To Get Help, Please Press X” The Rise of the Assistance Paradigm in Video Game Design

2011· article· en· W2185685865 on OpenAlexaff
­Carl Therrien

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAdventureExpansiveComputer scienceVideo game developmentVideo gameGame DeveloperMultimediaGame designVideo game designGame art designTransition (genetics)Human–computer interactionWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The first generation of video games are known to be tremendously challenging. On top of the classic “easy to learn, hard to master” arcade games, the development of the domestic market saw the rise of more expansive and varied game worlds, in computer RPGs or adventure games. This added complexity is often synonym with a more steep difficulty curve due to the amount of information to assimilate early on. In this paper, we will try to understand how game designers have organised the challenge and complexity of their games through the development of assistance systems: tutorials, check points, adjustable difficulty, etc. The historical evolution of these systems supposes a major change in the way players are addressed by the medium, from the highly competitive environment of early days to the seemingly more cooperative attitude of contemporary games.

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 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: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score0.377

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 head0.064
GPT teacher head0.284
Teacher spread0.220 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations9
Published2011
Admission routes1
Has abstractyes

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