Bibliographic record
Abstract
How do we construe and re:construe the (archi)textures of (written) life? What is belonging when identities are temporal and where naming remains elusive or unknown? This article plays writing collaborative writing, deconstructing textual hierarchies between the “main” text body and footnoted text as a means of interrogating ways identities are written/performed. It is inspired by correspondences between the authors, generated in relation to three previous works published in Qualitative Inquiry, James Haywood Rolling, Jr.’s “Messing Around with Identity Constructs: Pursuing a Poststructuralist and Poetic Aesthetic,” “Searching Self-image: Identities to be Self-evident,” and Lace Marie Brogden’s “Not Quite Acceptable: Re:Reading my Father in Qualitative Inquiry.” We share correspondences between academics, using spaces created in writing “between friends” while constantly becoming through the re:writing of our identities from no fixed address.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.076 | 0.034 |
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".