Arteria – A Regional Cultural Mapping Project in Portugal
Bibliographic record
Abstract
This paper discusses the relation between cultural mapping and participatory community cultural mapping, proposing the integration of a mobile device application (app) in the cultural mapping process of the Arteria project. This application aims to expand the notion of cultural appropriation by exploring how citizens can make crucial contributions to the cultural mapping process. This technology will evolve from and improve Arteria’s digital platform/website by boosting the processes of collection and registration of tangible and intangible cultural assets and the dissemination of registered cultural assets. The app will also enhance the connection among socio-cultural actors and improve the quality of community involvement in the cultural, social, and political dynamics of this cultural mapping project. To justify the need for such a tool, an overview of the project’s intent, objectives, and activities is presented, as well as its philosophy of intervention in local communities.Keywords: Arteria, community involvement, cultural mapping, cultural technology, mobile appRésumé: Cet article discute de l’introduction d’une application mobile dans le processus de cartographie culturelle du projet Arteria et met en évidence les liens entre planification culturelle et participation. L’application mobile vise à approfondir le sens de l’appropriation culturelle en explorant en quoi la participation citoyenne peut enrichir les processus de cartographie culturelle. La participation en ligne permettra d’enrichir les données et la plateforme d’Arteria en y ajoutant des références aux propriétés tangibles et intangibles de la culture urbaine. Cet article discute en quoi cette application mobile permettra d’enrichir les liens entre les acteurs socio-culturels et en quoi elle permettra également d’ajouter à la qualité de la participation et de l’implication citoyenne en tenant compte des dynamiques politiques de ces formes de planification.Mots clé: Arteria, participation de la communauté, cartographie culturelle, technologie culturelle, application mobile
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".