Collaborative Mapping as a Tool for Citizen Participation: A Case of Cultural Heritage Management in Rural Areas
Bibliographic record
Abstract
The role of citizens in the construction of knowledge is undergoing a clear transformation from a passive position, as mere observers and/or receivers, to an increasingly participatory role. This issue, which is directly related to governance policies as well as to the ICT revolution, can be seen in the field of cultural heritage and particularly architectural heritage management. The present paper aims to generate methodologies to involve citizens as active agents who must be involved in a real way in decision making concerning the protection and enhancement of cultural heritage. The results present the creation of a rural heritage interactive cartographic viewer as a collaborative mapping tool. The conclusions drawn position the citizens of rural, dispersed, or vulnerable areas as informers and builders of knowledge about the cultural and architectural heritage of their environment in terms of citizen science. At the same time, it strengthens the development of innovation strategies in the intervention, management, and communication of the existing dispersed heritage in rural areas.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".