“Frontstage” and “Backstage” in Heritage Performance: What Ethnography Reveals
Bibliographic record
Abstract
This paper considers how an ethnographer who studies heritage performance, in this case Me´tis fiddling and dancing, grapples with what is presented “frontstage” in public settings. The author uses the dramaturgical metaphors first offered by Goffman (1959) and that MacCannell (1973, 1976) later expanded in the analysis of touristic spaces. Unlike MacCannell the author does not view such performances as totally contrived in order to cater to an audience's preconceptions. Furthermore, the heritage performances the author studies and the touristic spaces that fed into MacCannell's analysis differ; they include performances for insiders as well as performances offered up to those assumed outside or less familiar with the cultural traditions being performed. The author contends that understanding and interpreting such public discourse requires more than just a semiotic reading of what these performers do and say frontstage. What ethnography ideally reveals is the complexity of local, familial as well as broader socio-political histories and allegiances.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".