The Libyan Desert as a Space of Experience: Richard A. Bermann as Chronicler of the 1933 Almásy-Expedition
Bibliographic record
Abstract
Abstract: Richard A. Bermann (1883–1939) was a prominent Austrian travel writer who wrote for prestigious newspapers in Berlin, Vienna and Prague and published a dozen travelogues and adventure novels set in foreign destinations from Brazil to the Sudan and Samoa. In March 1933, as part of a group around Count László Almásy, he embarked on an expedition into the largely unmapped heart of the Libyan Desert. Very quickly it became obvious that Bermann was physically and mentally overwhelmed by the exertions of desert exploration but also underprepared for the complexity of material and discursive practices accumulated in centuries of desert exploration. In spite of these challenges, Bermann published a series of articles about the journey for a Viennese newspaper, a book-length travelogue and a report for the Geographical Society in London. It was this report that inspired Canadian novelist Michael Ondaatje to write his global bestseller The English Patient . Richard A. Bermann (1883–1939) war ein bekannter österreichischer Reiseautor der für die großen Zeitungen in Berlin, Prag und Wien Reisereportagen verfasste, dazu Reisebücher und Abenteuerromane, die an weit entfernten Schauplätzen spielen. Im März 1933 brach er mit einer Gesellschaft, die von Graf László Almásy angeführt wurde, zu einer Expedition in eine bisher unkartierte Gegend der Libyschen Wüste auf. Bermann hatte Erfahrung in der Berichterstattung aus abgelegenen Weltgegenden, doch auf dieser Expedition stieß er an seine Grenzen. Ihm wurde bald klar, dass ihn die Anstrengungen der Wüste physisch und mental überforderten. Trotz dieser Herausforderungen verfasste er Artikel für eine Wiener Zeitung, einen Reisebericht in Buchlänge und einen Bericht für die Geographische Gesellschaft in London, auf dem der kanadische Schriftsteller Michael Ondaatje seinen Bestseller-Roman The English Patient basierte.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.018 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".