Bibliographic record
Abstract
Distributed by Good DocsProduced by Nancy Svendsen, Sharon Wood, and Christy McGillDirected by Nancy Svendsen2022, Streaming, 71 mins Pasang: In the Shadow of Everest intertwines a compelling narrative with well-executed cinematography to convey the age-old theme of triumphing over adversity. The film documents Pasang Lhamu Sherpa and her journey to become the first Nepalese woman to reach the summit of Mount Everest. With each attempt, Pasang faces physical, geographical, and societal barriers that, with the support of her family and community, she is eventually able to overcome. Interviews with Pasang’s family, friends, and colleagues show that she had set out to conquer more than Everest; her ultimate goal was to address the disparities between women and men in Nepalese culture. The quality of Pasang reflects a passion among the film’s crew. Each choice made in direction and editing is deliberate, leading to a cohesiveness between the film’s content and presentation. For example, the film alternates between interviews, archival footage, and visual aids based on the topic of discussion. This helps viewers to better contextualize the dialogue while still being immersed in the story. In addition, the film’s scoring helps to portray the emotions of its content, both in sound and silence. None of these choices distract from the film’s main message, but instead work towards informing and inspiring viewers. Pasang offers a universal appeal that allows it to fit into most film collections. In particular, institutions with an interest in women’s history and gender studies would benefit from making this film a part of their collection. This film is highly recommended, as it expertly conveys the struggles and successes of one woman and her never-ending climb towards gender equality. Awards:Charlie Fowler Best Adventure Film, Mountainfilm Festival; Honorable Mention, Jury Award, Documentary Feature, Bentonville Film Festival; Audience Award, AICEF Prize for Cross-Cultural Filmmaking, Clio Visualizing History Prize for the Advancement of Women in Film, Middlebury New Filmmakers Festival; Audience Award, Nevada City Film Festival; Audience Award, Best Film of Festival, BendFilm Festival; Best Film - Mountain Culture, Banff Centre Mountain Film & Book Festival; Best Spirit Award, Coast Film and Music Festival; Best Mountain Film, Kendal Mountain Festival; Best Mountain Culture & Nature Film, BBK Mendi Film Festival; Best Mountaineering Film, Festival Gorniskega Filma; Jury Special Mention, Vancouver International Mountain Film Festival; Best Feature Wild Spirit Award, New York Wild Film Festival; Mario Bello Award CCC - Club Alpino Italiano, Trento Film Festival
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.867 | 0.674 |
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".