Pennsylvania's border at Lake Champlain: Borders and contexts in colonial North America
Bibliographic record
Abstract
This essay stems from an idea that struck me as I stood in downtown Bedford, Pennsylvania, in the spring of 2004. Bedford is probably a familiar name to most North Americans (so many states have a Bedford, after all), and anyone who has traveled the Pennsylvania Turnpike may know the one I was in. Near Breezewood in the south-central part of the state and well within Pennsylvania's present-day borders but a little off the contemporary beaten path, it was once a summer retreat for Washingtonians, and before that a frontier outpost. This Bedford originated as one in a string of fortified supply depots built by the Forbes expedition as it methodically moved west in 1 758 to capture Fort Duquesne from the French. I happened to be in Bedford shortly after Dennis Mahoney announced this year's conference theme, and with that playing in the back of my mind as I stood in the center of town, I was struck by the consciousness people must have had in that midand late-eighteenthcentury frontier place of the immense backcountry stretching far into the continent, through which potential enemies could freely roam for hundreds of miles to burst suddenly upon them. Yet, as I also knew, people who lived in the southeastern heart of Pennsylvania considered Bedford, a hundred miles past the Susquehanna and two hundred from
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.019 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".