Bibliographic record
Abstract
“Korsakow, as a generative, processual program, is distinct to other interactive documentary platforms” (Miles, 2014, p.205) and affords a particular approach that I would like to call korsakowian and that I also recognize within platforms that attract far more users than Korsakow like for example YouTube. I agree with Judith Aston, who linked the term Metamodernism to interactive documentary at IFM2022 (Aston, 2022, p.7). I argue that the korsakowian approach can be considered a metamodern method and I raise the question if applying the korsakowian method (aware or unaware in doing so) advances metamodern thinking so that it can be seen as a “tool for thought” (Wiehl and Lebow, 2016, p.121), in the sense of a training tool, a tool that shapes thinking. The korsakowian approach can be viewed as a metamodern method that allows to approximate foreign ideas and explore them without implying definitive conclusions, even upon completion of the work. The artifact produced with a korsakowian approach remains in a perpetual state of openness, devoid of a predetermined narrative. I suggest that these kinds of open media works might effectively only be produced using generative, computer based tools that facilitate the organization of media and thereby allowing the ones using these tools to form unconscious associations. Employing tools that suggest metamodern methods could potentially shape the patterns of thinking of those utilizing them.Generative, computer based tools for organizing media are increasingly prevalent, particularly in the realm of social media — for example in the form of social media – tools and platforms that might encourage a korsakowian approach.
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 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.039 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".