Arctic National Wildlife Refuge : seasons of life and land : a photographic journey
Bibliographic record
Abstract
2003 Banff Mountain Image Award Winner and 2004 Gold Independent Publisher Book Award in Environment, Ecology, and Nature The most comprehensive, photographic documentation of the biodiversity and indigenous cultures of the Arctic National Wildlife Refuge One hundred and twenty full-color photographs by author and photographer Subhankar Banerjee, winner of the prestigious Alaska Conservation Foundation Daniel Housberg Wilderness Image Award Essays by Peter Matthiessen and David Allen Sibley, among others The Arctic National Wildlife Refuge (ANWR) is America's Serengeti, comprising 19.8 million acres of land in the northeast corner of Alaska and adjoining Ivvavik and Vuntui National Parks in the Yukon Territory in Canada. Photographer Subhankar Banerjee, in collaboration with six essayists, presents a portrayal of a unique landscape made up of equal parts beauty and hazard. The Arctic National Wildlife Refuge, one of the last intact ecosystems on earth, is being impacted by forces that may change its existence forever: global warming and the encroachment of modern society through the potential for oil drilling. Jimmy Carter, George Schaller, and Bill Meadows narrate the story with essays that delve into the history of the Refuge, the political battles -- past and present -- and the fragility of the ecosystem. Wildlife biologist Fran Mauer writes of the areas geological and geographical uniqueness while Debbie Miller describes the cultures of the Inupiat Eskimos and the Gwich'in Athabascan Indians. David Allen Sibley explores the prolific bird life and migrations at the refuge with an eye toward the delicately balanced ecology of the region. Peter Matthiessen, reflecting on his journey through the Refuge with Banerjee, passionately defends the need to preserve these lands and the people and the wildlife they shelter. Visit the photographer's website at www.subhankarbanergee.org
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.097 | 0.014 |
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".