Bibliographic record
Abstract
Salvaging Hope is a dystopian adventure novel set in 2024 in which corporations are managing a privatized version of Calgary, Alberta, akin to the other major Canadian cities. In this world, corporate control of major Canadian cities, privatization of services, for-profit health care, and exploitation of fines for high profits reign supreme. The first-person narrator is a neurodivergent & disabled queer woman in her late twenties exploring the intimate connections of identity and the power of an inclusive community against the city’s expanding social barriers and attitudes. Disabled characters in science fiction historically have not been portrayed as hero-capable in storytelling without stigmatization, stereotyping their existences, or curing them of their otherness. In Salvaging Hope, fluid expressions of non-linear time are showcased through the narrator’s perceptions about herself and the expectations of others in the world. Disability is not a monolith, and this manuscript aims to showcase a sampling of diverse human beings experiencing a world. Salvaging Hope’s dystopian society, based on the realities of our own, operates unapologetically in its exclusion of disabled and neurodivergent lives with its barriers to our survival.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".