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Record W2959488721 · doi:10.24908/iqurcp.13289

Use of Progressive Rock in Donkey Kong Country (1994)

2019· article· en· W2959488721 on OpenAlexaffvenue
Brooke Spencer

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2019
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsMelodyChord (peer-to-peer)PunkBluesHistoryVisual artsMusicalComputer scienceArtArt historyDatabase

Abstract

fetched live from OpenAlex

Whereas most of Nintendo’s music from the 1990s used basic looping structure and simple chiptune-reminiscent sounds, Donkey Kong Country (1994), composed by British composer David Wise rather than by Nintendo’s in-house composition team, featured texturally more complex music, including features characteristic of the 1970s/80s progressive rock style such as short repeated melodies and chord progressions with layering (Collins 44). For example, in “Fear Factory” (Figure 1), we hear a repeated chord progression of (VI, iv, i) underneath a faster eighth-note melody. Very little harmonic movement occurs and the focus is more on the melodic layers that occur in this top voice. In addition, “Fear Factory” includes unconventional punk, “mechanic/industrial”, and “glitch” noises that emphasize melodic content (https://www.youtube.com/watch?v=v18pEFQb3EM&t=45s). As William Cheng discusses in Sound Play, the use of such unconventional sounds often contribute to a feeling of dissociation and alienation in the player, and create a divide between diegetic (that is, music the characters are aware of) and non-diegetic (that is, “background” music) soundscapes (Cheng 98-9). While this is not a direct element of prog-rock, both industrial and prog-rock music styles feature a strong focus on texture. Collins speculates that this may have been an attempt by Nintendo to capitalize on the ‘edgier’ market of other game producers such as Sega (Collins 46). In this paper, an analysis of form, melodic structure, and instrumentation from Donkey Kong Country’s “Treetop Rock” and “Fear Factory” will demonstrate features atypical of Nintendo style, which normally features catchy tunes, simple instrumentation, and pop-inspired harmonies. Figure 1: e-: VI iv I VI ivBibliography Cheng, William. Sound Play: Video Games and the Musical Imagination. The Oxford Music/media Series. Oxford: Oxford University Press, 2014. Collins, Karen. Game Sound an Introduction to the History, and Practice of Video Game Music and Sound Design. Cambridge: MIT Press, 2008.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.106
GPT teacher head0.350
Teacher spread0.243 · 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
Published2019
Admission routes2
Has abstractyes

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