From Native Pines to Diasporic Geese: Placing Culture, Setting Our Sites, Locating Identity in a Transnational Canada
Bibliographic record
Abstract
In Canada, as elsewhere, introspective and nostalgic views of community and nation-state are being challenged by the impacts of globalism and cosmopolitanism. The impact of these transformations is acute in the context of Canada, where a liberal multiculturalism is transmuting into a hybrid pluralism. Current strategies of identity formation have to accommodate a hybridity that is being fostered by an ever-increasing diasporic population for whom “lived-in places” exhibit transnationalist connections. Too often, established mnemonic tropes relate to past iconic values and norms of the nation-state, even though they are no longer connected with emerging new values that search for new modes of expression. This paper discusses the crucial role of the arts and heritage in this local anchoring of the transnational polity, arguing that symbolic landscapes become sites where new values are contested and traditional iconic values are challenged.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".