Toward modeling the social edition: An approach to understanding the electronic scholarly edition in the context of new and emerging social media
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores building blocks in extant and emerging social media toward the possibilities they offer to the scholarly edition in electronic form, positing that we are witnessing the nascent stages of a new ‘social’ edition existing at the intersection of social media and digital editing. Beginning with a typological formulation of electronic scholarly editions, activities common to humanities scholars who engage with texts as expert readers are considered, noting that many methods of engagement both reflect the interrelated nature of long-standing professional reading strategies and are social in nature; extending this frame work, the next steps in the scholarly edition’s development in its incorporation of social media functionality reflect the importance of traditional humanistic activities and workflows, and include collaboration, incorporating contributions by its readers and re-visioning the role of the editor away from that of ultimate authority and more toward that of facilitator of reader involvement. Intended to provide a ‘toolkit’ for academic consideration, this discussion of the emerging social edition points to new methods of textual engagement in digital literary studies and is accompanied by two integral, detailed appendices, published in Digital Humanities Quarterly under the title ‘Pertinent discussions toward modeling the social edition: Annotated bibliographies’ (http://www.digitalhumanities.org/dhq/vol/6/1/000111/000111.html): one addressing issues pertinent to online reading and interaction, and another on social networking tools.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it