Bibliographic record
Abstract
We read differently outside. Discussing works by two experimental poets, a. rawlings and Christine Stewart, this essay draws on geocritical and ecocritical methodologies alongside Indigenous theories that link language, story, and land to consider how an outdoor pedagogical practice attunes readers not only to the spatial dynamics of language, but also to the linguistic dynamics of place. While the colonial, sedentary structures of traditional classrooms shut out the world, immersing us in literary realms as though they were separate from our physical realities, reading outside makes us viscerally aware of how land and language shape one another. Beyond the walls of our classrooms and homes, we can feel our entanglements with the land, its histories, and other species. In the colonial spaces of Canada, which continues to grapple with considerable ecological and social harms, cultivating such awareness matters: while reading outside is not enough to save us from the environmental crises we are facing or assuage colonial grief and guilt, doing so brings us closer to the living edges of language, which is where new forms of attention might nourish a more mutually sustaining relationship between land and words.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.023 |
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".