Paysages identitaires et ruralité de proximité: regards croisés à Petit‐Saguenay (Québec)
Bibliographic record
Abstract
Au Québec, plusieurs groupes d'acteurs travaillent à structure? un pmjet d'avenir pour le monde rural. La question identitaire traverse leurs réflexions. Le rapport au territoire est conçu comme un trait spécifique de l'identité rurale contemporaine. Par ailleurs, le paysage offre un cadre de référence pertinent à l'analyse de cette identité façonnée par les acteurs. Cela suppose que, d'un point de vue théorique, le paysage soit envisagé selon une approche construc‐tiviste, qui va au‐delà des formes visibles pour englober aussi les références aux pratiques territori‐ales et les intentions des acteurs sociaux, de même que des dimensions immatérielles, telles les représentations et l'affectivité. En d'autres mots, le paysage est id défini comme un construit social. En confrontant ce cadre de référence à une enquête réalisée dans un village d'une région du Québec, nous avons constaté que les acteurs locaux lisent le paysage à partir de critères endogènes, c'est‐à‐dire propres à leur vécu territorial. Pour ces acteurs, le paysage agit à la fois comme agent de médiation et de communication de même qu'il participe à la construction de l'être‐ensemble. In Quebec, there are a number of groups actively engaged in structuring future plans for the rural milieu. The question of identity runs throughout their reflections, and the relationship between actors and territory is seen as a specific trait of contemporary rural identity. Furthermore, the concept of landscape provides a pertinent frame of reference for the analysis of this identity. From a theoretical point of view, this presupposes that landscape be envisaged according to a constructivist approach which would go beyond the visible forms to include territorial practices and intentions of the social actors as well as the immaterial dimensions such as the perceptions. In other words, landscape is seen as a social construction. This frame of reference was used to analyse observations gathered in a village situated in an outlying region of Quebec, and it was noticed that the local actors perceive the landscape according to endogenous criteria, i.e.: criteria specific to their real‐life territorial experience. For these actors, the landscape is both an agent of mediation and communication and a participant in the construction of a whole, a way of being or living together (“l'etre‐ensemble”).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".