Tunisian Music: The Soundtrack of the Revolution, the Voice of the People
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
10 million inhabitants, most of whom I found to be both welcoming and generous. 1 The North borders the Mediterranean and boasts sandy beaches with beautiful aqua blue waters and the capital of Tunis. The South treasures the mysterious and vast Sahara desert and lush oases with their numerous palmeries. It was in this country, 5,000 km from my home here in St. John's, Newfoundland and Labrador, that I found myself at the end of May 2012. I was interested in the opportunity to immerse myself in a part of the world I knew little of, do field research for the first time, talk to first-hand witnesses concerning one of the most important world events of the early second millennia, and delve into the relationship between history and music. These interests culminated in a proposal that I created and submitted to the Summer Research Program at the College of the Holy Cross where I was working on my Bachelors of Arts in French and in Music. I was thrilled to find out that I was accepted to participate in the program sponsored by the Andrew W. Mellon Foundation. As a Mellon Fellow, I spent 5-1/2 weeks conducting research under Holy Cross music professor and librarian Alan Karass. This was Alan's tenth trip to Tunisia as he was working on his Ph.D. in Ethnomusicology on the Douz Festival in the country's south. He
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it