Bibliographic record
Abstract
i began my writing life as a poet, publishing two poetry collections in my twenties.I stopped writing for nearly a decade after the births of three children.My husband and I were building a house for our family on 8.5 acres of wooded land on a peninsula northwest of Vancouver.I created a garden and learned the art of quilt-making.I expected to have time to write again once my children were in school and I expected to return to poetry, but I was surprised to discover that poetry no longer wanted me.I had the impulse to write, I had ideas to explore, materials accumulating in my mind as my quilting basket accumulated scraps of cotton, but I didn't have a shape for my thinking any longer.The lines I wrote continued past the point where a poet would consider the stanza, the lyric, complete.At first I tried to wrangle them, contain them, but one day I just let those lines continue, as prose, maintaining a certain rhythm but given the freedom of the wide space on a page.One line led to another, then another.Their purpose was not to create fiction but instead to make a map of my own reflections, main roads and secondary roads, river systems, mountains, and beautiful circled stars for settlements.One line led to another, a thread leading me into the heart of meaning I hoped would be there, a little knot at the centre.I remember how exhilarated I felt to discover I was writing something that I came to understand was an essay.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.340 | 0.173 |
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".