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Record W4414131201 · doi:10.1080/17411912.2025.2547333

<i>Jaww:</i> conceptualising Tunisian musical air

2025· article· en· W4414131201 on OpenAlexaff
Rachel Colwell

Bibliographic record

VenueEthnomusicology Forum · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsUniversity of Alberta
FundersUniversity of California BerkeleyAmerican Institute for Maghrib Studies
KeywordsMusicalTourismField (mathematics)Perspective (graphical)

Abstract

fetched live from OpenAlex

Based on musical and sensory ethnography across Tunisia, this article explores the interconnected dimensions of jaww, a complex musico-cultural concept encompassing atmosphere, social environment, climate, and mood. For both performers and listeners, jaww functions as: (1) a connection between the air of different settings across time and space, (2) a conduit for the transmission of privileged musical knowledge, (3) an immersive, multisensory medium infused with sounds, smells, and spirits; and (4) a pervasive intersubjective feeling. While special attention is given to the jaww of ma’lūf (Tunisian-Andalusian music), the atmospheres of other Tunisian musical traditions are also considered. The role of jaww in evoking nostalgia is examined within the broader context of Andalusi musics, and comparisons are drawn with related North African and Middle Eastern concepts such as ṭarab (musical ecstasy) and ḥāl (spiritual or emotional state). Finally, the article considers how region, descent, social class, and national identity shape the musical experience of jaww.

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 score0.031
Threshold uncertainty score0.062

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 studies0.0030.006
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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
Published2025
Admission routes1
Has abstractyes

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