Bibliographic record
Abstract
Charles Taylor has called ours an “Age of Authenticity”, and authenticity is a popular object of scholarly examination, not least in anthropology. A considerable number of scholars have even proposed models for multiple “authenticities”. None, however, has brought a modified Peircean theoretical tool-kit together with ethnographic evidence that “the natives know” that there are many authenticities. This article seeks to fill that gap. Working with Peirce’s model of the sign and with postmodern theories of originals and replicas, we draw on Wilce’s Finnish fieldwork to analyze what we consider clear evidence of four authenticities arising in recent debates surrounding traditional Karelian lament and particularly highly organized attempts in Finland to “revive” the practice. We call performances arising out of the revival “neolaments”. We treat authenticities as strictly relational, metasemiotic, and ideological phenomena. Authenticities that appear salient to actors on the revivalist scene may involve the following relationships : that between any neolament performance and any particular Karelian lament performances, with the question being whether the former is adequately “traditional” (i.e. relationship between replica and original); between a particular lament performance and the generic essence of that which makes lament a lament (i.e.token and type); between a lament performance and emotion – a relationship ideologically construed as “expressive” (i.e. sign and object); and finally, a relationship between some sort of dynamic interpretant of particular old Karelian laments (lament1) and new dynamic interpretants generated in and through new lament performances (lament2 or habitual participation in such performance) that in some way replicates the old dynamical interpretant (interpretant1and interpretant2).
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.080 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".