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Record W4294199688 · doi:10.4000/volume.10189

Hatfield and the North (1974) : une synthèse en équilibre

2022· article· fr· W4294199688 on OpenAlexaff
Jacopo Costa, Philippe Lalitte, Pierre Michel

Bibliographic record

VenueVolume ! · 2022
Typearticle
Languagefr
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMusée de la Civilisation
FundersAgence Nationale de la Recherche
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Le groupe Hatfield and the North figure parmi les plus représentatifs de la Scène de Canterbury : ses deux albums en constituent une production importante. Le premier album de 1974, simplement intitulé Hatfield and the North, est abordé ici essentiellement et selon plusieurs approches successives : contextualisation, forme des morceaux, analyse de l’enchaînement des morceaux pour chaque face du vinyle sur la base de la théorie des attentes musicales, les apports des différents musiciens et leurs spécificités dans le jeu instrumental, la pratique des métriques complexes dans « Shaving is boring » et « Lobster in Cleavage Probe », les différentes approches stylistiques des quatre membres du groupe et les interactions entre leurs conceptions musicales propres. Les contributions de trois musicologues convergent en une analyse détaillée et diversifiée des caractéristiques précises de cette musique. Le second album, The Rotter’s Club, est abordé en fin d’article, ainsi que le devenir de chacun des musiciens après la dissolution du groupe. Un entretien avec Dave Stewart (en fin d’article) porte sur les questions de composition et de production du disque. Une telle exploration de cet album permet au lecteur de mieux saisir la richesse de cette production et de la situer dans un contexte plus large, en l’occurrence celui de la Scène de Canterbury.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.357
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.017
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.018
GPT teacher head0.238
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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2022
Admission routes1
Has abstractyes

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Same venueVolume !Same topicNeuroscience and Music PerceptionFrench-language works237,207