Bibliographic record
Abstract
Brown, Don. Drowned City: Hurricane Katrina and New Orleans. Boston, MA: Houghton Mifflin Harcourt, 2015. OverDrive Read. Web. 21 Mar. 2016.While it wasn’t the “big one” that meteorologists had predicted for New Orleans, the havoc wreaked by Hurricane Katrina’s landfall on August 29th, 2005 was monstrous in proportion. Many will surely remember the news stories, but Drowned City gives the reader an as-it-happened view of the various hardships faced by the residents and rescuers. Stories from all walks of life are here - the heroic acts of residents with boats who saved their neighbours, the hospital patients kept alive by friends and family after generators lost power, the forced separation of pets from owners, and the trains and cargo ships turned away as a result of mishandled organizational efforts. Throughout the story, Brown subtly explores the racial politics of the event, including Gretna’s police force turning away displaced New Orleanians, and George W. Bush comfortably surveying the chaos and squalor in the city below from his private jet. Once the streets had drained, the dead were accounted for - all 1,833 of them.Drowned City has already been featured on year-end lists from Kirkus, School Library Journal and Publishers Weekly. Rather than approach the story with a harshly dogmatic invective, Brown’s compassionate, matter-of-fact prose exposes the situation for what it was - a catastrophe that impacted millions of lives, featuring both acts of heroism and gross incompetence. Matching the text are the author’s gritty watercolours, crafted with a muted palette that effectively sets the tone of the book. This combination is used to illustrate the struggles that dogged survivors: stifling heat and stench without the reprieve of air conditioning.New Orleans’ recovery story remains complex; though rejuvenated tourism spending far surpasses pre-Katrina levels, its African American populations have dropped significantly since the storm. Brown’s book evocatively captures the event that changed everything for this great city and is a prototypical example of the power of graphic novels for historical subjects. A must for library collections.Highly recommended: 4 out of 4 starsReviewer: Kyle MarshallKyle Marshall is the School-Aged Services Intern Librarian for Edmonton Public Library. He graduated with his MLIS from the University of Alberta in June 2015, and is passionate about diversity in children's and youth literature.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.133 | 0.083 |
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".