Fear and Loathing Worldwide [Paperback]:Gonzo Journalism Beyond Hunter S. Thompson
Bibliographic record
Abstract
For more than 40 years, the radically subjective style of participatory journalism known as Gonzo has been inextricably associated with the American writer Hunter S. Thompson. Around the world, however, other journalists approach unconventional material in risky ways, placing themselves in the middle of off-beat stories, and relate those accounts in the supercharged rhetoric of Gonzo. In some cases, Thompson's influence is apparent, even explicit; in others, writers have crafted their journalistic provocations independently, only later to have that work labelled "Gonzo." In either case, Gonzo journalism has clearly become an international phenomenon. In Fear and Loathing Worldwide, scholars from fourteen countries discuss writers from Europe, the Americas, Africa and Australia, whose work bears unmistakable traces of the mutant Gonzo gene. In each chapter, "Gonzo" emerges as a powerful but unstable signifier, read and practiced with different accents and emphases in the various national, cultural, political, and journalistic contexts in which it has erupted. Whether immersed in the Dutch crack scene, exploring the Polish version of Route 66, following the trail of the 2014 South African General Election, or committing unspeakable acts on the bus to Turku, the writers described in this volume are driven by the same fearless disdain for convention and profound commitment to rattling received opinion with which the "outlaw journalist" Thompson scorched his way into the American consciousness in the 1960s, '70s, and beyond.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".