Bibliographic record
Abstract
treaty negotiation, Timothy Pickering, a key figure in the development of early U.S. food policy, misremembered past instances of Native and non-Native hunger while giving a "history lesson."At this meeting on the Tioga River (which ran between present-day Pennsylvania and New York), Pickering met a group of Senecas, one of the six tribes of the Iroquois Confederacy."When the white people came to this Island, the Indians lived chiefly by hunting and fishing," he explained to Cornplanter, one of the Iroquois negotiators.On this "island" of North Amer i ca, "the white people immediately began to till the ground, to grow corn, wheat, and other grain . . .and to raise abundance of cattle, sheep and hogs."In the past, Pickering explained, "the Indians continued to follow hunting and fishing, growing only a little corn.They were often in want of food," and "exposed to great hardships." 1 Pickering met Cornplanter and the other Senecas in the midst of a fight against hunger that began before colonists arrived in North Amer i ca and ended in the 1810s.In 1791 Pickering was a newcomer to Iroquois diplomacy.He had only been working as a negotiator for a year, and the learning curve had been steep. 2He started his job during a momentous shift in relations between Natives and non-Natives, when the United States, after a de cade of weakness and uncertainty, was trying to gain the upper hand in its dealings with Indians.As a result, his speech to Cornplanter conveyed an inaccurate historical picture.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".