Bibliographic record
Abstract
Chris Anderson G'02 likes to be on the move.At one time he traveled the country racing snowboards on the national amateur circuit.These days shooting pictures keeps him in motion-it's been that way ever since he took a photography class as an undergraduate at Humboldt State University in his native northern California."It was a sea change in perception of what my life would be," Anderson says."That summer I went to Israel and got caught in the worst flash floods in years.I took pictures and thought, 'This is really cool.I could do this for a living.' " Since then, he's worked at newspapers in Vermont and New Hampshire; visited Poland, where he began a long-term project documenting a group of Jewish expatriates returning to their homeland and then journeying to Israel; and has continued his travels in Israel and other parts of the Middle East."I have a need to move," he says."I appreciate having a home base, but I'm not able to stay for long."This past year, as a graduate student in the Newhouse photography program, Anderson called Syracuse home."It was the most amazing learning experience I've ever had because it was so intense," he says."I ate, slept, and lived photography.It made me crazy, but I can't imagine a better way to learn."As part of his Newhouse experience, he participated in a weekend shoot documenting the lives of people in the suburban Syracuse community of Fayetteville-Manlius; took photos in Lockerbie, Scotland, for a photojournalism project that Newhouse faculty and students are working on; and was involved
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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; both teacher heads agree on what is shown here.
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".