Bibliographic record
Abstract
The article presents the initial steps of a research-creation project that has been developed within the scope of the Federal University of Espírito Santo, in Brazil, and whose main objective is to give visibility to socio-environmental conflicts in the metropolitan region of Grande Vitória, capital of Espírito Santo, from the development of interactive and immersive audiovisual works. At first, a field research was carried out in a specific territory of the capital – the Jesus de Nazareth neighborhood – in order to identify some of these local conflicts and the community's ways of acting in an attempt to solve the problems. The problem proposed by the ongoing research can be summarized as follows: using research-creation as a methodology and work process, how to develop interactive, immersive and collaborative multimedia works that make it possible to increase the visibility of socio-environmental conflicts existing in a given territory – in this case, the metropolitan region of Greater Vitória – and, in parallel, promote scientific dissemination and the popularization of science? The research has a multidisciplinary character and brings together the following fields of study: i) research-creation and digital humanities; ii) new communication technologies, immersive (augmented/virtual reality) and interactive media; iii) socio-environmental conflicts in the metropolitan region of Greater Vitória (ES) and their impacts on the population; and iv) scientific dissemination. In addition to the objectives and expected results – to increase the visibility of socio-environmental conflicts and social injustices, research data on these issues and to disseminate possible solutions –, the research is also justified by the possibilities of learning and experimenting with technological resources on the part of of professors and students of a public university in Brazil. The article brings data about the main conflicts already mapped in the Greater Vitória region, information about the visited community and also theoretical notes on the concept of socio-environmental conflict, understood in a broad way, but which includes the articulation between the environment and social relations. The text also presents the principles of creation as research and its use as a methodological process. The current stage of the research consists of collecting and selecting data from scientific research banks and reviewing the literature.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.009 |
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".