Being Irish on the Prairies: Repertoire, Performance, and Environment in Oral History Narratives of Winnipeg Irish Canadians
Bibliographic record
Abstract
This thesis applies Diana Taylor's concept of repertoire to oral history interviews with ten first generation Irish Canadians living in Winnipeg who emigrated between 1957 and 2012.It argues that traditional performances, such as music and dance, have acquired a provenance with particular histories.This has made them both meaningful and politically contentious expressions of Irish identity.Memory tensions emerged when the performances were integrated into a new repertoire in Canada.Taylor's concept is modified and applied to embodied encounters with landscape and weather.As experiences of a new place are incorporated into a spatial repertoire, they become infused with emotional significance, and emigrants' stories about visiting Ireland, surviving Manitoban winters, or driving across flat prairie spaces, communicate feelings of displacement and belonging.Accompanying this thesis is a website which further explores emotional memories in these interviews through an audio exhibit (www.beingirishontheprairies.ca).descriptions of significant actions which constitute a repertoire give insight into migration experiences and relationships with the past. All of my interviewees migrated to Canada in the post-war period -a time inIreland that was characterized by ebbs and flows in migration, both out of and onto the island.The difficult economic times of the 1950s and late '70s and '80s saw rises in net emigration while the '60s and the Celtic Tiger of the '90s saw a switch to net immigration into the country.Political conflict in Northern Ireland reached its peak between 1971 and 1976, galvanized in part by civil rights movements occurring in America and elsewhere in the world.This conflict, known as the Troubles, stimulated both internal migration and emigration.13 The interviewees involved in this project migrated to Canada in three distinct waves: the 1950s, the 1970s and 1980s, and a recent migration wave which started in 2011.14 Winnipeg, in contrast to Ireland, experienced a steady influx of migration during this time.In the immediate post-war period there was large migration from Europe to major Canadian cities, including Manitoba's capital.In addition, people in rural areas of all the provinces were moving to urban centres, which contributed to a steady increase in Winnipeg's population.In the 1970s and the decades that followed, the largest migrant populations coming to Winnipeg were from parts of Latin America, Asia, Africa, the Caribbean, and the Mediterranean, as well as significant numbers of First Nations peoples moving from reserves to the City.15 At present, a substantial proportion of Winnipeg 13 Fitzgerald and Lambkin, Migration in Irish History, 224, 236, 248.14 Mary Gilmartin, "The changing landscape of Irish migration, 2000-2012," (working paper,
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".