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Record W7067954858

Music and Ideas of North

2021· book· en· W7067954858 on OpenAlexaboutno aff

Bibliographic record

VenueHuddersfield Research Portal (University of Huddersfield) · 2021
Typebook
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsThe ImaginaryMusicalFocus (optics)DreamExpression (computer science)Popular musicMusical expression
DOInot available

Abstract

fetched live from OpenAlex

Northern identities in different regions, cultures and communities – particularly when constructed as foils to 'The South' – have been the focus of considerable attention among cultural historians, literary scholars and commentators, several of whom are represented in this collection. Yet despite its prominence in the discourse of north-south relations, the role of music in producing and articulating notions of northernness has not been discussed in detail. Rugged yet fragile, communal yet solitary, conservative yet radical, the real and imaginary spaces of the north have inspired many different musical responses, perhaps the most enigmatic coming from pianist Glenn Gould in his radio documentary The Idea of North (CBC, 1967): 'I've read about it, written about it, and even pulled up my parka once and gone there. Yet like all but a very few Canadians I've had no real experience of the North. I've remained, of necessity, an outsider. And the North has remained for me, a convenient place to dream about, spin tall tales about, and, in the end, avoid.' This collection represents the first extended dedicated exploration of music and ideas of north, drawing on northern English, Scottish, Canadian, Scandinavian and Finnish identities, as well as north-south dynamics in a European context, to uncover connections and contradictions in the musical experience and expression of northernness across the globe.

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)0.003
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.052
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.046
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.135
GPT teacher head0.381
Teacher spread0.246 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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