Meltdown \nAn Investigation of a Seascape in Two Film Forms
Bibliographic record
Abstract
In my thesis exhibition I juxtapose two distinct forms of cinematic representation of landscape, specifically depicting a grounded iceberg and tidal pools off coastal Newfoundland. In a screening room, a four-minute time-based documentary portrays workers on a repurposed fishing boat, ice harvesting. In an adjacent gallery, a cinematic media installation includes enlarged underwater imagery of tidal pools, and shots of icebergs projected onto and refracted from acrylic discs. In the gallery area, viewers move through at their own rate, following their personal drift of attention as they choose. This invites an embodied process of audiovisual assimilation, opening up opportunities for affective response to the image environment. In the supporting thesis paper, I have drawn upon the texts of Hito Steyerl, on horizon and aerial cinematography, John Stilgoe on horizon, seascape and landscape, Brian Massumi on embodiment and affect, and Eugenie Brinkema on cinema and affect. Through the juxtaposition of narrative time-based and expanded cinema, I invite spectators to reflect from different vantages on the impact of environmental changes on water, including its economic, community and personal consequences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".