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Record W4393305261 · doi:10.1109/tg.2024.3380253

Playtesting Box Art: Player Perceptions and Expectations

2024· article· en· W4393305261 on OpenAlexaff
Hamna Aslam, Pavel S. Tishkin, Eleonora Ilina, Joseph Alexander Brown

Bibliographic record

VenueIEEE Transactions on Games · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMartial Arts: Techniques, Psychology, and Education
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsPerceptionPsychologyVisual artsArtNeuroscience

Abstract

fetched live from OpenAlex

An essential component of the game is the box it comes in. Though it seems like a small object, it is the first door to the world it encapsulates in itself. Box makes an impression, and perceptions are associated with it. This paper investigates board game's box art and related perceptions. A disappointing box art results in the game being left un-purchased on the store shelves. This is not the only consequence. An undesirable impression from the box art remains with the player, although they enjoy the game. While the games have the potential to convey intended benefits, the box is the only chance for game designers to evoke buyers' attention, if the game has not been advertised by other means. It is significant to understand how players associate with box art, their perceptions, and their desirability. This paper has investigated box art design for its desirability, the first impression it conveys, and perception of it. We present a series of questions that help test the box art of board games. The questions are broken down into categories to investigate different aspects of the box art. The participants have also drawn the box art for a particular game setting that informs about their preferred design.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.777
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.029
GPT teacher head0.350
Teacher spread0.322 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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