Bibliographic record
Abstract
During the exhibition session, we propose to view a VR experimental documentary of 20’. The VR film is made after a three-year practice-based collaborative research on mothers and children living together in a condition of imprisonment. The objective is to understand their different points of view about the confined spaces they are - or have been living - and how they endured the challenges of raising children in prison, and also which are their hopes and dreams for the future. This Ph.D. research mixes theory and practice, with the intent to analyze the production of the VR film, made combining live-action shooting and animation Objectives and methodology: The aim is to discuss which are the potentialities and also limitations of immersive storytelling applied to visual anthropology in closed contexts such as prisons, with the collaboration of multiple approaches and forms of art, like animation. VR filmmaking process helped to research confinement - in confined places - during the pandemic. The objective is to understand their different points of view about the confined spaces where they have been living in the past, and how they endured the challenges and the crises they faced during their childhood and motherhood, worsened by the pandemic. The attempt to hear their own voices and their perspective following Mirzoeff’s ideas (Mirzoeff 2011, 2015) brought me and a group of artists and practitioners to experiment and employ different forms of art and methodologies, such as illustration, animation, digital storytelling, photo-elicitation and anthropological observational fieldwork. My hypothesis is that the VR filmmaking process – more than the normal ‘flat’ documentary cinema – helped to build and share a collaborative process (between academics, practitioners and the protagonists of the research). Furthermore, I (Rossella Schillaci) think VR technology helped to support the participation of children and youth, envisioning new possibilities for interdisciplinary collaborations and to better listening to children’s ideas of participation, and expression of their point of view about the present, past and mostly future, representing their thoughts, fears and dreams. Intended results: reflection and debate about ethical problems, the potentiality of using new technology in the research and also in the dissemination of the results. How new media can facilitate and open a broad discussion about the topics that involved not only academics but also practitioners and decision-makers? The VR film will be available for participants. An excerpt will be available for publication, together with a paper about the making process, the methodology, the challenges faced and the results obtained.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".