Introduction: Autobiography 2.0 and quick media life writing
Bibliographic record
Abstract
Abstract This special issue brings together research on the self-in-relation from both a narratological angle and from the perspective of gender studies, queer theory, postcolonial and transnational studies. The articles featured here discuss new and shifting understandings of how we define life writing practices differently in an age of online expressions in various verbal and visual forms, and through the lens of family, broadly defined. In this introduction, we establish the concept of ‘autobiography 2.0’ as a particular practice of life writing that modulates identity and kinship through the use of digital media. This introduction addresses key questions we were asking ourselves and the individual contributors as we set out to theorize the impact of social media and the mediation of family and kinship ties on life writing genres: How is relationality mediated differently in an online context and how does this impact our ideas about family and kinship? What issues of privacy and property are connected to the online presence of digital memoirs? Which different reading practices do we need to bring to the multi-layered online text of autobiographies 2.0? How does reading online autobiographies create kinship ties among readers? How are traditional modalities of identity (race, gender, ability, class, etc.) destabilized by online life writing?
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 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".