Bibliographic record
Abstract
This project follows the path blazed by such scholars as Jodi Byrd (Chickasaw Nation of Oklahoma), Glen Coulthard (Yellowknives Dene First Nation), Vine Deloria Jr. (Oglala Sioux), Lawrence Gross (White Earth Chippewa), Kwes Kwentin (Musqueam), Audra Simpson (Mohawk), Inés Talamantez (Mescalero Apache), and Zoe Todd (Red River Métis/Otipemisiwak), who have all argued for the value in using Indigenous epistemologies as critical theories in a largely non-Indigenous academic context. Following their research and their practice, my project uses the Anishinaabe epistemology of Mino-Bimaadiziwin, or “the good life,” to read Margaret Atwood's speculative “ustopian” (dystopia / utopia) novel, MaddAddam. While scholars have approached the novel, as well as the trilogy as a whole, in terms of post-structuralism, post-colonialism, post-humanism, feminism, and trauma narratives, few (if any) have addressed the novel in terms of Indigenous ways of seeing and being part of an interconnected and interdependent world. Some readers may question the relevance of Indigenous studies in this novel due, perhaps, to the near-absence of non-white characters in the trilogy; others may question the relevance of Margaret Atwood to the conversation of Indigenous studies in light of the criticisms brought against her fiction and non-fiction for their (stereotypical or appropriative) representation (or lack thereof) of Indigenous people and cultures and due to her participation in debates regarding the supposed claims of Native identity made by Canadian authors. Nevertheless, this paper argues that reading MaddAddam in terms of Mino-Bimaadiziwin highlights the epistemological significance of the novel's inventive use of discontinuous narrative, polyphony, and ambiguous endings, as well as the non-anthropomorphic use of non-human voices and discourse, both of which are illustrative of the novel's determined turn towards a non-anthropocentric and non-speciesist post-apocalyptic society. While these points share commonalities with the theories raised in post-structuralism and posthumanism, reading the novel in terms of Anishinaabe epistemologies not only illuminates the critical value of these ways of seeing the world, but highlights the ways in which non-Indigenous philosophies like post-structuralism and post-humanism are indebted to those marginalized fields of theory which preceded them, often by centuries. As such, this project has three goals: to provide an in-depth narratological analysis of one of Atwood's most popular novels; in doing so, to offer an alternative theoretical approach to the novel which includes Native epistemologies; and thus, to do the valuable and necessary work of ontological and social decolonization by challenging the commonly accepted wisdom of who produces theory and to whom it is applied.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".