Transforming Identity and Space Through Relational Lines in Louise Erdrich’s Books and Islands in Ojibwe Country and Lisa Bird-Wilson’s Probably Ruby
Bibliographic record
Abstract
This paper challenges the Western, colonial notion of lines as divisive boundaries and instead, cultivates a reading practice that reveals the transformative potential of the line. In my analysis of two texts written by Indigenous authors, I reflect on the connection between space and stories by considering how each protagonist depicts their surroundings and its consequent effects on their identities through the framework of the relational line. In her memoir Books and Islands in Ojibwe Country (2003), Louise Erdrich (Ojibwe) travels through the land of her ancestors and in her descriptions of rock paintings, she remarks how the line “is a sign of power and communication” as it relays ancestral knowledge (45). I confirm Erdrich’s assertion in my interpretation of the representation of lines within Erdrich’s memoir as agents of interaction. This paper considers the reciprocal potential of lines in Erdrich’s depictions of land and the land’s ties to her identity, which she illustrates as inseparable from tradition and results in her reclamation of space. Because of the framework’s inherently interactive nature, I extend my analysis to a second text: Lisa Bird-Wilson’s (Métis and nēhiyaw) novel Probably Ruby (2020). My decision to analyze these two texts in tandem relates to how they enact Daniel Heath Justice’s “process of becoming” through their nuanced depictions of identity and contrasted renderings of space. I propose that Erdrich’s memoir highlights the process that Ruby encounters, wherein one’s connection to land and ancestral stories is unknown because of their removal and distance from their Indigenous heritage, which occurs through Ruby’s adoption, and results in a more abstract network of relationships and setting. Erdrich’s text prompts a compelling discussion of Ruby’s story, since it responds to the difficulty of a more abstract reclamation, with Ruby unable to navigate a physical space filled with an understanding of tradition that Erdrich is granted. I argue that through their movements that extend and return, the lines in these texts illustrate the protagonists’ reclamation of their spaces while also challenging the boundaries of lines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".