The last polar bear : facing the truth of a warming world
Bibliographic record
Abstract
Scientists agree that by the end of this century the polar bear will be the first mammal threatened with extinction due to climate change. The Last Polar Bear is the first book to fully document that story.The continued survival of these magnificent white bears in their warming, and melting, Arctic world is uncertain, yet their fate is also a wake-up call compelling us to act now to stem global warming. Through Steven Kazlowski's unparalleled imagery, the most critical environmental issue of our time is brought to life.The Last Polar Bear places the reality of climate change in our hands. We see the plight of the polar bear, an animal already feeling the detrimental effects of our reliance on fossil fuels, as its icy habitat melts.Over the course of the last six years, wildlife photographer Steven Kazlowski has photographed the polar bear in its wild habitat, from Hershel Island in Canada to Point Hope in Alaska. The Last Polar Bear pairs his intimate images with anecdotes about his Arctic adventures, as well as authoritative essays about the polar bear in the context of climate change.Alaska based writers Richard Nelson, Charles Wohlforth, Nick Jans, and leading USGS polar bear biologist Steven C. Amstrup draw on decades of experience in the Arctic to cover the biological, cultural, and anthropological aspects of climate change. Dan Glick, long-time correspondent for Newsweek, addresses the history of climate change while Frances Beinecke, president of the Natural Resources Defence Council, and Theodore Roosevelt IV offer perspectives on activism and politics.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".