Défricheurs d’eau: An Introduction to Acadian Land Reclamation in a Comparative Context
Bibliographic record
Abstract
This paper seeks to place the dyke-building and land reclamation accomplishments of the 17thand 18th-century Acadians in as wide a context as possible. Numerous authors state that what the Acadians achieved was unique, or at least unique in North America. In this paper we see comparable examples from Europe, Africa and North America that should allow us to begin to place the Acadian achievement in a more balanced context. The end result is that we see that there were a number of peoples in different areas that reclaimed land and/ or developed agricultural practices that involved dyking procedures. What is particularly noteworthy about the Acadians is that they achieved what they did on the basis of a community-based approach and in a setting where the tides are the highest in the world. Resume Cet article cherche a replacer les reussites des Acadiens des XVIIe et XVIIIe siecles dans le domaine des constructions de digues et des reclamations de terres dans le plus large contexte possible. De nombreux auteurs ont affirme que ce qu’ont realise les Acadiens etait unique, du moins en Amerique du Nord. Dans cet article, nous comparons des exemples provenant d’Europe, d’Afrique et d’Amerique du Nord, ce qui devrait nous permettre de replacer les realisations des Acadiens dans un contexte plus equilibre. Nous constatons finalement qu’un certain nombre de peuples dans differentes regions ont revendique des terres et/ou ont developpe des pratiques agricoles impliquant des constructions de digues. Mais ce qui est particulierement remarquable chez les Acadiens est que leurs realisations se sont faites sur la base d’une approche communautaire et a l’endroit ou l’amplitude des marees est la plus elevee au monde.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".