Bibliographic record
Abstract
From the critically acclaimed author Ausma Zehanat Khan, A Deadly Divide is the devastatingly powerful new thriller featuring beloved series detectives Esa Khattak and Rachel Getty. In the aftermath of a mass shooting at a mosque in Quebec, the local police apprehend Amadou Duchon--a young Muslim man at the scene helping the wounded--but release Etienne Roy, the local priest who was found with a weapon in his hands. The shooting looks like a hate crime, but detectives Esa Khattak and Rachel Getty sense there is more to the story. Sent to liaise with a community in the grip of fear, they find themselves in fraught new territory, fueled by the panic and suspicion exploited by a right-wing radio host. As Rachel and Esa grapple to stop tensions shutting the case down entirely, all the time, someone is pointing Esa in another direction, a shadowy presence who anticipates his every move. A Deadly Divide is a piercingly observed, gripping thriller that reveals the fractures that try to tear us all apart: from the once-tight partnership between detectives Esa and Rachel, to the truth about a deeply divided nation -- Provided by publisher
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.024 | 0.025 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".