Bibliographic record
Abstract
A common question asked about the web 2.0 by the offline population is: "What do people do there?" The paper addresses this question with respect to Paul Ricoeur's narrative theory of the self. According to his essay Life in Quest of Narrative, a person drifts through time experiencing events happening to them, but none of it is actually lived when it is not "recounted" or "storied". In this light, "storytelling may be said to humanise time by transforming it from an impersonal passing of fragmented moments into a patter, a plot ,a mythos". Blogs and sites like Facebook represent the most recent development in the human attempt to weave this "mythos". A profile page and a tweet are first and foremost stories that appear to its critics "truncated or parodied" by design "to the point of being called micro-narratives or post-narratives", and to it s advocates"multi-plotted, multi-vocal and multi-media". The paper introduces notions of e-Self and e-Narrative, examines their dangers and benefits, and concludes that "the advent of cyber-culture should be seen not as a threat to storytelling but as a catalyst for new possibilities of interactive, non-linear narration".
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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; 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".