Landscape/mindscape/langscape: The ephemerality of the digital and of the real in Marlene Creates’s video-poems for ice and snow
Bibliographic record
Abstract
Abstract The present essay aims at illustrating Marlene Creates’s web project Brickle, nish, and knobbly (2015), as a key example of Eco-Digital Humanities. First of all, it is a digital work of art made of ice images. Besides, it is also a digital archive meant to salvage a linguistic treasury of local idioms that both name and describe all types of snow and ice formations in Newfoundland, Canada. Therefore, the present analysis proves the special quality and inevitable ephemeral status of this project, for it constitutes a multimodal and multimedia web-archive, subject to possible erasure, or obsolescence in the face of new computer programmes and platforms developments. The archive is also an open instrument for everybody’s use: a digital audio-visual (poetic) dictionary, that ultimately functions as a challenge to climate change effects, that might dissolve both the ice formations and the language that accompanies them. Since the real world is no less ephemeral than the world of the web, this contribution also proves how Marlene Creates’s artwork envisions and embraces an ecological salvaging of our present and future landscape, mindscape, and langscape.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.003 |
| 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".