Canadian picture books: shaping and reflecting national identity
Bibliographic record
Abstract
A nation's literature has traditionally been seen as a reflection of the values, tensions, myths, and psychology that identify a national character. Benedict Anderson defines a nation as "an imagined community." He maintains that the members of a nation never know each other, meet each other, or hear each other, yet they hold in common an image of who they are as individuals in community with each other. Undoubtedly, one of the building blocks of national identity is literature. Sarah Corse writes that literature is "an integral part of the process by which nation-states create themselves and distinguish themselves from other nations." She then makes the case that national literatures not only reflect a nation's unique identity, but also play an active role in shaping that identity. A strong Canadian national identity has only recently developed. Until the mid-twentieth century, Canadian identity was seen as an amalgam of blurred French, British, and American values and cultures. The mutual distrust present between the French-speaking and English-speaking cultures created a tension in Canada that has lasted from the eighteenth century to the present. Both French and English nationalists, according to Ramsay Cook, reject "the validity of the concept of political nationhood and cultural duality which has been central to the Canadian experience." They do not believe that a culturally divided community can produce a common national 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.018 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.059 | 0.005 |
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".