Bibliographic record
Abstract
This chapter considers Lenny Kohm’s life story, from growing up in the Seattle Jewish community during the postwar years through his career as a jazz drummer and member of the countercultural scene in the San Francisco Bay area. It then follows him to Sonoma, California, where he moved in 1977 and later pursued a career as a photographer. Much of the chapter focuses on what Kohm called his epiphany—a 1987 trip to Alaska and the Yukon that inspired his refuge activism. That summer, just as the Ronald Reagan administration called for drilling in the coastal plain, Kohm visited the Arctic Refuge, hoping to take pictures that he could sell to <italic>Audubon</italic> magazine. A chance stopover in the Gwich’in community of Arctic Village, Alaska, followed by a trip to Old Crow, Yukon, completely changed his perspective on the issue. Returning home, Kohm desperately wanted to figure out how to make a difference in the Arctic Refuge struggle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".