Bibliographic record
Abstract
Dying in the Southwest explores the relationship between the individual, the collective, and the larger socioeconomic systems that provide the foundation of the places we call home. The collection focuses primarily on the city of Windsor, Ontario, which was known as “Ground Zero” during the 2008 Financial Crisis. Due to high rates of unemployment, stagnant wages, and low desirability for investment, the people of Windsor-Essex County found themselves trapped within a constantly shaken snow globe. Inside this microcosm, habits and routines were broken and patched over hastily in order to survive. The poems follow the small, personal dramas that play out alongside and within the macroeconomic crisis. Dying in the Southwest captures the many attempts made to endure, adapt, or escape the city. Stagnation and failure pervade these attempts. Misdirection, error, and unwillingness to change lie at the core of both the cause and effect of the Financial Crisis. Throughout the collection, Dying in the Southwest maintains a balance of hope and cynicism for a city so ravaged by large-scale systems beyond its control.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".