The war reporting of Robert Fisk: relentlessly exposing the horror
Bibliographic record
Abstract
Global Literary Journalism: Exploring the Journalistic Imagination (Peter Lang, of New York) brings together the writings of 22 academics focusing on literary journalism in a wide range of countries and regions including Canada, Finland, India, Ireland, Poland, Sweden, Latin America, the UK, the United States and the Middle East.The University of Lincoln is well represented: Jane Chapman, Professor of Communications, focuses on the journalism of Arundhati Roy, Rupert Hildyard, Principal Lecturer in English, writes on John Lanchester, Nick Nuttall examines the gonzo writings of Hunter S. Thompson, PhD student Florian Zollmann delves into the John Pilger archives, while another PhD student, Anna Hoyles, explores the early journalism of Moa Martinson. Rod Whiting looks critically at Ernest Hemingway’s career as a journalist – while John Tulloch’s chapter on Gordon Burn is titled ‘Journalism as a Novel: The Novel as Journalism’ and Richard Keeble writes on the war reporting of the Independent’s award-winning Robert Fisk.The final chapter, by Susan Greenberg, of Roehampton University, and titled ‘Slow Journalism in the Digital Fast Lane’ examines literary journalism in the age of the internet.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.021 | 0.017 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".