Bibliographic record
Abstract
This special issue of the Interactive Film and Media Journal constitutes the first of two issues dedicated to the IV International Interactive Film and Media Conference, held online in June 2022 and co-organized by Hudson Moura (Toronto Metropolitan University, Canada), Heidi Rae Cooley (University of Texas at Dallas, USA), Anna Wiehl (University of Bayreuth, Germany) and Stefano Odorico (Technological University of the Shannon, Ireland / Leeds Trinity University, UK). As tangential as it may seem, the IFM conferences are an opportunity to reflect on the scholarly field of interactivity, offering a platform for academics and practitioners to broaden the field across disciplines. The conference titled: Interactive Epistemology, Listening, and Ecomedia clearly demonstrated that interactivity does not just have a newly rediscovered popularity in film and media, but it is also omnipresent in a multidisciplinary context, from cultural productions such as games, films and books to audience perception such as streaming, virtual reality and real-time; from intellectual publications such as news, hypertexts, social media to virtual world economy such as cryptocurrencies.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".