Mediation, Then and Now: Ang Tharkay’s <em>Sherpa</em> and <em>Memoires d’un Sherpa</em>
Bibliographic record
Abstract
The memoir of Ang Tharkay, a well-known Sherpa mountaineering guide and leader from the early years of Himalayan mountaineering, poses several problems for contemporary readers. The book, Memoires d’un Sherpa (A Sherpa’s Memoir), fell into obscurity after its publication in 1954, but was translated from French and reissued as Sherpa in 2016. Since the original text was heavily mediated by its editor, translator, and transcriber, can we read Sherpa as Ang Tharkay’s life story? I propose that we must, and that we can if we do this sensitively, with an eye for the types of mediation found in each edition and whose needs they serve. Therefore, we need to think about what mediation is, whose interests its serves, and how it works in the making and reading of Sherpa. Mediation in memoir discourse affects any account, past and present. Knowing how mediation works in Ang Tharkay’s memoir is essential to hearing what climbers from Nepal had to say in the 1950s, and how it is possible, and imperative, to hear their voices now, in all their complexity, in order to challenge romantic ideas about Sherpas which persist in mountaineering writing. In so doing, we can connect the stories of early Sherpa climbers about labor issues to the concerns Sherpa climbers write about today.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".