Bibliographic record
Abstract
Universal in scope, yet focusing on recognizable Canadian places, this collection of essays connects individuals’ love of nature to larger social issues, to cultural activities, and to sustainable technology. Subjects include activism in Cape Breton, eco-feminism, Native perspectives on the history of humans’ relationship with the natural world, the inconsistency of humankind’s affinity with nature alongside its capacity to destroy, and scientific and traditional accounts of evolution and how they can come together for the welfare of Earth’s ecology. These essays encourage us to break down the power-based divisions of centre versus marginal politics, to talk with our perceived enemies in environmental wars, to consider activism as a personal commitment, and to resist the construction of a “post-natural” world. Using a combination of personal memoirs and formal essays, Every Grain of Sand seeks to involve readers in the extraordinary places they inhabit—and usually take for granted—and will appeal to both the general reader and to students in humanities, social sciences, and environmental studies. It is unique for its presentation of entirely Canadian perspectives on ecology and environmental issues.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 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".