‘Twitter’: Practice in writing: A recipe for creativity & creative interpretation
Bibliographic record
Abstract
This paper will explore how the way we read on the screen can create new forms of collaborative writing online. With reference to our ‘Twitter: Practice in Writing’ workshops in London 2014 and Vancouver 2015. As a younger generation move swiftly from print to pixel, reading no longer becomes deliberate and concentrated but rather a scan for information as our eyes follow an F-shaped pattern. Screen-reading encourages rapid patternmaking, provoking action, whereby words are merged with images. From scroll to moveable type, will twitter ‘novels’ give rise to twitter brains? How does it affect what we read and write? Has this change been recognized in the publishing industry?
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.032 |
| Scholarly communication | 0.025 | 0.024 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.011 |
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".