Bibliographic record
Abstract
As part of a multi-sited international research project (Montreal and Kinshasa) organized around the idea of audience-based research, the “Ethnographies of Listening” research team attempted to go beyond previous studies of the Congolese popular music industry by conducting systematic surveys throughout Kinshasa from June 2002 to August 2005. In the early phases, a large amount of time was spent considering the question of representativeness: how to be sure interviews were conducted in a random and representative manner. Subsequently, the reality of field research and the constraints imposed by limited communication and financial resources led to discussions about the very notion of representativeness and whether or not it was pertinent to the study of popular music. Local and foreign researchers disagreed about the importance of having equal representation in the survey sample and selection of sites. This difference of opinion led to useful discussions about the supposedly inclusive nature of this “collaborative” research project and how its evolution coincided with what some team members referred to as a democratic moment in national politics.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.047 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.016 | 0.034 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".