Bibliographic record
Abstract
In Meaningful Pasts, Russell Johnston and Michael Ripmeester explore two strands of identity-making among residents of the Niagara region in Ontario, Canada.First, they describe the region's official narratives, most of which celebrate the achievements of white settlers with a mix of storytelling, rituals, and monuments.Despite their presence in local lore and landmarks, these official narratives did not resonate with the nearly one thousand residents who participated in five surveys conducted over eleven years.Instead, participants drew on contemporary people, places, and events.Second, the authors explore the emergence of Niagara's wine industry as a heritage narrative.The book shares how the survey participants embraced the industry as a local identifier and indicates how the industry's efforts have rekindled the residents' interest in agriculture as a significant element of regional heritage and local identities.Revealing how the profiles of local narratives and commemorations become entwined with social, cultural, economic, and political power, Meaningful Pasts illuminates the fact that local narratives retain their relevance only if residents find them meaningful in their day-to-day lives.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.587 | 0.296 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".