On Fertile Ground: Locating Historic Sites in the Landscapes of Fundy and the Foothills
Bibliographic record
Abstract
Since the 1972 National Museums Policy announced its goals of “democratization and decentralization,” national historic sites have been marked by a trend toward regionalization. While scholars have focused on the nationalizing impetus of twentieth-century historiography before 1970, subsequently there have been consistent efforts to incorporate local environmental and cultural diversity into the “family” of national sites. This paper demonstrates this system-wide trend by comparing historic sites in the Bay of Fundy and the Alberta foothills. In both places, designation has evolved from the two-nations narrative of French-English rivalry, in seventeenth-century forts or fur trade posts which could integrate far-flung localities, thereby claiming transcontinental space as national territory. Interpretation now credits local ecological factors with shaping the course of historical events, and acknowledges in situ resources. In addition, Parks Canada has involved groups such as the Acadians or the Blackfoot, whose claims of “homeland” jostle the naturalized Canadian boundaries affirmed by the older national narrative. There are other complications, raised by revisions in public history; notably, these sites continue to play a role in the marketing of place – in a long tradition of using the landscape as an entrée to tourism – and they are not yet conceived in regional groupings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".