Bibliographic record
Abstract
Background\n“Kam", meaning "Shaman" in old Turkish, is a film expressing the primal, potent energy of the female body via long exposure pixilation/2D animation techniques. The film investigates how the improvisation of a dancer can be recorded via long exposure technique and translated into animated film language to create a manifesto around the selected theme.\n\nContribution \nThe film deconstructs & reconstructs movement using the optics field's light recording principles. To record light, first photographers had to expose their subjects for a long period of time, creating traces of movement on the frame. This effect was often considered as undesirable. The film consciously uses this artifact to condense the motion of the dancer in individual pictures, which also allows a stream-of-consciousness approach while creating a new dance flow, which is later combined with 2D animations. The primitive drawings on top of long exposure photographs take form of interventions to the narrative, creating a new, more pronounced layer of expression enforcing the rebellious, transformative energy of the female body. With this film, the combination of long exposure pixilation & 2D animation has been explored for the first time to capture and translate a dance performance.\n\nSignificance\nKam is selected to be screened in three international festivals (Xsection, Animated Dance Festival, and Experimental Dance and Music Festival) in USA and France, It was equally selected for screening in Toronto’s Yonge-Dundas Square (YDS) in annual outdoor movie series called Virtual City Cinema, featuring best of short films from around the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".