What's past is prologue: Assessing the interplay of history, identity, and sociopolitical attitudes in Canada
Bibliographic record
Abstract
Our social identities are built and maintained through a variety of cultural tools that help us feel a sense of cohesion with the groups to which we belong. Although Canadians belong to a wide variety of distinct cultural groups, something that can tie them together is a shared sense of history. In this dissertation, I consider the important role that social representations of history play in Canadian identity and how identity and history work together to inform contemporary sociopolitical views. Manuscripts 1 and 2 are based on data that was collected from Canadian universities in Toronto, Halifax, and Québec City. Manuscript 1 examines the values and identities of undergraduate students from these three regional-linguistic groups. We found that while participants from the two English-speaking regional groups had a strong sense of Canadian identity, the Québec City participants did not and instead held a stronger provincial identity. Manuscript 2 focussed on the content of young Canadians’ social representations of history and their historical biases. We again found a contrast between our English-speaking regional groups and Québec City, whereby the former seemed to have a less unified set of collective memories and the latter held a consistent narrative about Québécois nation-building and cultural conflict. We also found that all three groups held a positivity bias about Canadian history that was related to Canadian identity. Manuscript 3 was based on two community samples of Canadians who were presented with biased historical narratives to influence their current sociopolitical attitudes. Although we found no evidence of this effect, we did discover that Canadians believe that historical events related to marginalized groups are much more important than historical events that aren’t directly related to such groups. Evidence of a positivity bias was found again, whereby positive events related to historically oppressed groups were considered especially important. Altogether, this dissertation enhances our understanding of Canadian identity and the contemporary sociopolitical values of Canadians. It also offers original insights for the social representations of history literature by cataloguing the unique collective memories of a multicultural country and providing evidence of a robust relationship between history and social identity.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".