Bibliographic record
Abstract
"L.M. Montgomery's writings are replete with enchanting, yet subtle and fluid depictions of nature that convey her intense appreciation for the natural world. At a time of ecological crises, intensifying environmental anxiety, and burgeoning eco-critical perspectives, L.M. Montgomery and the Matter of Nature(s) repositions the Canadian author's relationship to nature in terms of current environmental criticism across several disciplines, introducing a fresh approach to her life and work. Drawing on a wide range of Montgomery's novels as well as her journals, this collection suggests that socio-ecological relationships encompass ideas of reciprocity, affiliation, autonomy, and the capacity for transformation in both the human and more-than-human worlds, and that these ideas are integral to Montgomery's vision and her literary legacy. Framed by the twin themes of materiality and interrelationships, essays by scholars of literature, law, animal studies, anthropology, and ecology examine place, embodiment, and difference in Montgomery's works and embrace the multiplicities embedded in the concept of nature. Through innovative critical approaches, L.M. Montgomery and the Matter of Nature(s) opens up conversations about humans' interactions with nature and the material environment."...
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".