Annotated Bibliography of Oral History in Canada: 1980 – 2012
Bibliographic record
Abstract
Oral history in Canada has flourished over the past two decades. There is a lack of knowledge, however, regarding the depth of publications in the field and the numerous scholars across the country who are engaged in oral history methods. This annotated bibliography is intended to act as a research guide for interdisciplinary scholars in the field. The bibliography was completed in the fall of 2012 by Dr. Kristina R. Llewellyn and her research assistant Dana Nowak. The authors conducted extensive searches in social sciences and humanities library databases for published works in the field of oral history with a Canadian subject focus. Keyword searches associated with oral history were inclusive of, but not exclusive to, oral tradition, narrative, storytelling, and folklore. Some additions were made to the bibliography based on the authors’ knowledge of other published works. The annotations are those provided by the authors and/or publishers (some with minor grammatical changes). The bibliography is only a partial list of Canadian oral history publications. The search methods particularly limited the findings for chapters in edited collections and articles published in journals outside the social sciences and humanities. Oral History Forum d’histoire orale is committed to updating this bibliography as the field continues to develop.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.051 | 0.131 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.012 |
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".