Bibliographic record
Abstract
The short stories in this collection explore the effects of having belonged to the Canadian subculture of treeplanters. Most of the main characters are ex-treeplanters: young, or to their dismay, not so young, middle class women and men who have experienced hard, seasonal labour in the Canadian wilderness. They may have taken up planting in the first place as a means to pay for university or travelling, or to support their music or art, but most of them returned to it year after year, finding in it something more compelling than just the money. Now, they have quit, or are on the brink of quitting planting, in some cases due to the physical injuries caused by the job. They are trying to get a life outside of planting but are crippled by their connections to their past planting experiences. The protagonists' attempts to grapple with these connections--connections which take the form of relationships, fears (of bears or nine-to-five jobs), environmental or class awareness--are often ambiguous or ineffective. But by the end of the stories their view of planting, whether utopic or dystopic has been tested. They are forced to see how their view affects the people around them and the choices, or lack of choice, it provides.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.461 | 0.246 |
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".