Les « communautés de relations au paysage », l’expérience socio-spatiale avec le territoire comme nouveau cadre pour l’analyse des populations rurales
Bibliographic record
Abstract
Can we still set farmers against non-farmers, locals against new-migrants in the contemporary rurality ? Proposing the notion of communities of relationships with the landscape as a new framework for the analysis of the rural populations, this article intends to show the contribution of the landscape studies to this debate. This notion suggests to group together people on the basis of their experience with the rural landscape in order to exceed the socio-demographical categories defined a priori. A case study conducted in the intensive agricultural areas of the south of Québec illustrates how it is applied in a qualitative research which brings up to date two typologies based on ideal types. The results shows a productive rural always attentive in this territories but with faces more complicated that their apparent spatial and social homogeneity hint at. Thus, without reducing the differences between groups of rural populations, the notion of community of relationships with the landscape seems to be particularly heuristic in order to offer a more exactly reading of the challenges link to the recomposition of social spaces in the rural.
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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 | 0.002 | 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 | 0.008 | 0.028 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".