Anna Sergi, Alexandria Reid, Luca Storti, and Marleen Easton, Ports, Crime and Security: Governing and Policing Seaports in a Changing World by Chris Madsen
Bibliographic record
Abstract
Reviews 145 on the subject, as well as to help explain and/or suppress some myths that have emerged in the more than 150 years since the disaster (ix).In re-examining primary source materials, he provides a new perspective on the sinking; for example, how newspapers approached the event, the investigations, and the hearings and influenced subsequent attitudes about it.Despite his extensive research into Sultana's fate, Salecker does not offer his own theory on what happened or indulge in speculation and mythmaking.Instead, he lays out the available evidence and allows readers to draw their own conclusions.The author's extensive use of first-hand accounts, secondary sources, newspaper reports, trial transcripts, and numerous other sources, means those interested in pursuing additional research for academic study will find much to offer.The emphasis on the human element of the Sultana tragedy reminds readers at all levels that this is a very human story.Any references to technical aspects of steamboat construction or operations, or the dynamic conditions that influenced travel on the Mississippi River appear within the context of their role in the disaster.Destruction of the Steamboat Sultana the Worst Maritime Disaster in American History, provides an accessible and comprehensive account of the events surrounding the loss of the Sultana, and the events that followed.It is both a gripping introduction to the subject and a thorough, wellresearched, account, accompanied by enough source materiel to inspire future investigations.While exploring the sinking and its aftermath, he touches on other historical influences at the time and debunks decades worth of speculation and mythmaking that have grown up around the Sultana disaster.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".