Wearing My Ancestors: At the Crossroads of Genre
Bibliographic record
Abstract
Formerly presented by a new mother-in-law to a young bride after her wedding, the Transylvanian Saxon Haube, or embroidered velvet costume hood or bonnet, from Nösnerland in northern Transylvania appears on the surface to be folk costume, but its intersecting elements of folk art, rite of passage, and even folk belief prove that one category is not sufficient to understand the significance of this example of folklore text as I use it in the present. I apply Alan Dundes’ concept of “Text, Texture, and Context” (1980) while examining the Haube I own, possible methods of its construction and the material from which it is made. I use autoethnography to extract the messages I portray when wearing it in comparison to what is communicated through variants on display. The Haube is no longer worn by many married women in Canada, yet through examination of the one that was passed on to me after my wedding, I study the nuances of wearing, in comparison to displaying, this piece of folk clothing in order to discuss how folklorists might begin to categorize it. Finally, I consider how I transpose the personal significance of a tradition that was not designed for contemporary use through present-day donning and display, from its use in Transylvania to itsshowcase in Canada today.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".