Bibliographic record
Abstract
This interdisciplinary exploration of voice seeks to open a space for the nondiscursive performative power of vocality in qualitative research. In the first part, I focus on anthropology and ethnographic practice to identify the ways in which “voice” gets muted when transformed by scriptocentrism (see Dwight Conquergood) into a conceptual abstraction or a metaphor. Given anthropology’s colonial legacy and the implication of ethnographers in what Anthony Kwame Harrison defines as the project of literatizing non-literate societies, I argue that the potentially scriptocentric dimension of ethnographic practice must be taken seriously in light of the travels of ethnography across disciplines and its increasingly widespread usage within qualitative inquiry. In the second part, I foreground philosopher Adriana Cavarero’s critique of the devocalization of logos in Western philosophy and its analysis by interdisciplinary voice studies scholar Konstantinos Thomaidis, who investigates the systematic exclusion, marginalization and silencing of voice through Eurocentric constructions of logos as reason and as language. By means of an imaginary visit to ancient Greece, I scrutinize Plato’s anxiety vis-à-vis performance through an ethnographic encounter with the Ion, a dialogue between Socrates and a well-known champion of rhapsodic contests. On the basis of this performative ethnographic fieldwork, I suggest that conducting qualitative research on the significance and relevance of vocality today requires listening to, engaging with, and learning from the voices of ancient and contemporary oral cultural practitioners.
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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 | 0.053 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".