Apprenticeship as method: embodied learning in ethnographic practice
Bibliographic record
Abstract
Apprenticeship, the process of developing from novice to proficiency under the guidance of a skilled expert, varies across cultures and among different skilled communities, but for many communities of practice, apprenticeship offers an ideal ethnographic point of entry. For certain kinds of anthropological fieldwork, such as studies of bodily arts, apprenticeship may offer an essential research method. In this article, three anthropologists discuss their experiences using apprenticeship in fieldwork and consider the practical and theoretical issues of apprenticeship as a site of ethnographic inquiry. As a channel for achieving social inclusion, apprenticeship offers anthropologists opportunities to navigate and chart interpersonal power, access to emic types of knowledge, first-hand experience of the pedagogical milieu, and avenues to acquire cultural proficiency. Because apprenticeship itself includes mechanisms to socialize emerging skill, such as disciplining the generation of variation that is inherent in each individual’s rediscovery or reinvention of skill, apprenticeship encourages our subjects to collaborate with us by allowing them to critique the ethnographer’s performance and provide feedback in familiar, locally-meaningful ways.
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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 | 0.088 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.007 | 0.052 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".