Making sense of territorial changes: affective and moral dimensions of place attachments and meanings
Bibliographic record
Abstract
For the last five decades, several approaches to sense of place have been developed and used to better understand the complex dynamics between multiple coexisting spatial practices and experiences. The relationship between territorial changes (place change) and senses of place is still under investigation. Our research method contributes to the inquiry about sense of place and place attachment by combining concepts and practices from two research communities: environmental psychology and pragmatics of attachment approaches. The study was conducted in a rural community in northern Senegal and used a mixed-methods approach that included questionnaires, interview-photos, and a participatory theater device. The observations revealed a plurality of attachments and meanings associated with both the territory and the places that form it. Above all, they revealed multiple elements implicated in the construction and evaluation of place attachments and meanings. The results showed that, while diverse entities are simultaneously involved in the production and evaluation of sense of place, the acceptance of change by the members of a community as a whole depended on maintaining affective relationships that engage them and respecting the moral values they hold. Based on the results, we used the framework of affective arrangements to characterize the complex set of relationships involved in the attachment dynamics and territorial changes.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".