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Record W7161795088 · doi:10.82308/6791

Folk music and the construction of community: Southern Ontario in the 1970s

2015· dissertation· en· W7161795088 on OpenAlexaboutno aff
Rachel Avery

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFolk musicMusicalEthnomusicologyFolk songFolk cultureFolk religion

Abstract

fetched live from OpenAlex

Tandis que la périodisation courante considère que la musique folk était un genre peu dynamique dans les années 1970, cette thèse documente et analyse la scène effervescente de musique folk du sud de l'Ontario durant cette décennie. Les diverses composantes de cette scène et les idées qui s'y rattachent sont examinées à l'aide d'entrevues effectuées auprès de vingt-cinq participants issus de ce milieu. La majorité des musicien-ne-s deviennent à cette époque des auteurs-compositeurs-interprètes plutôt que des interprètes de musique traditionnelle. Par conséquent, les concepts qui définissent la musique folk et les notions d'authenticité qui la caractérise se transforment. Par l'activité musicale, des communautés de musicien-ne-s et d'auditeurs se sont formées et ont façonné une scène régionale. De plus, les participants ont développé un sentiment d'appartenance à une communauté imaginée plus vaste. En plus d'avoir contribué au caractère authentique de cette scène, les lieux qui ont accueilli les concerts folk ont été des points de rencontre importants dans le paysage musical régional et perdurent dans les mémoires personnelles et collective.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.651

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0180.008
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.038
GPT teacher head0.291
Teacher spread0.253 · 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
Published2015
Admission routes1
Has abstractyes

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