People You Grew Up With: A Novel
Bibliographic record
Abstract
People You Grew Up With is a coming-of-age novel. Told in the voice of its protagonist, Alma Montanya, the narrative begins in the near future on the picturesque coast of Italy where Alma is travelling as a newly single woman in her thirties. One morning, drinking a cappuccino and scrolling on her phone, she stumbles upon news of a devastating wildfire that struck the small prairie town of her childhood, Pheasant Creek, Alberta. As Alma is prompted to reckon with her memories of this place, the narrative shifts back in time to mid- to late-2000s when she was a teen in rural Alberta. By thus interweaving scenes from Alma’s present reality with scenes from her earliest experiences with love and loss, People You Grew Up With asks, how do the people and places that we know in our youth shape who we become? To what extent can we move on from these formative experiences and to what extent are we bound to them?
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".