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Record W4411393809 · doi:10.5206/notabene.v18i1.22192

Tunes from the Land: Can Folk Music Cultivate Awareness and Respect for Nature?

2025· article· en· W4411393809 on OpenAlexvenueno aff
Emma Robinson

Bibliographic record

VenueNota bene · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAestheticsPsychologyArt

Abstract

fetched live from OpenAlex

This basic qualitative research study explores ecoliterate approaches to instrumental music education, focusing on cultivating environmental awareness through using folk music to address a disconnect from nature in educational contexts in the United Kingdom. Drawing from both research literature and personal experience, the study involved planning and delivering violin lessons designed to foster ecoliteracy in young people. By focusing on the intersection of environmental and folk music education, the project aimed to develop a closer relationship between students and their environment: in particular, a sense of place. Two violin students, aged 12 and 14, were selected as participants for the study. Data was collected through informal post-lesson conversations, which were audio-recorded and transcribed, alongside lesson observations and reflections, then analysed using thematic analysis. The key themes that emerged were: Oral Tradition, Connection to Place, Instruments, Teaching Environment, and Student Development. Examining the students' experiences provided insights into how instrumental music teachers can incorporate ecoliteracy into their pedagogy. This study offers practical suggestions to foster ecoliteracy, such as the use of oral learning, improvisation based on natural sounds, and exploration of local music. These findings will be of interest to music educators seeking to enrich their curriculum with the aim of supporting a more ecologically aware generation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.999

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)0.0000.000

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 head0.083
GPT teacher head0.265
Teacher spread0.182 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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