En attendant le céleste héritage: frameworks and methodologies for the archival preservation of Franco-Manitoban folklore
Bibliographic record
Abstract
Folklore occupies an interesting space within archives. It can be difficult to capture, and yet it is so culturally important that not doing so seems like an oversight. Archivists have explored in detail the concepts of collective memory and archives as places of memory, yet folklore remains an under-examined topic. This thesis seeks to address some of these gaps where they relate specifically to the Franco-Manitoban community. Using existing scholarship surrounding community archives and collective memory, it delves into the ways in which Franco-Manitoban folklore is currently represented within local archives and the challenges these archives face in making this folklore accessible. It argues that while the challenges may be significant, there is equally significant value in overcoming these challenges. To do this, I use the holdings at the Centre du patrimoine as a case study in the presence of folklore, folk culture and oral history in heritage institutions as it stands today. Throughout this exploration, I apply archival theory in order to examine how community archives can overcome some of the most pressing issues they are facing in regard to folklore-related records and highlight the efforts already being made towards this end. This thesis also attempts identify Franco-Manitoban representation within the larger sphere of online folklore. I discuss the difficulties of defining archives within the vast realm of cyberspace, as well as the advent of Internet-born folklore. Reflecting on the limitations of search engines and online archives, I examine the scattered and sparse nature of Franco-Manitoban folklore on the Internet, observing that there is still much work to be done in this respect.
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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 | 0.030 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.028 | 0.016 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| 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".