Discreet Openness: Scholars’ Selective and Intentional Self-Disclosures Online
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
Research into emergent forms of scholarship focuses on academics’ use of technology for learning, teaching, and research. Very little attention has been paid in the literature to scholars’ uses of social media to disclose challenging personal and professional issues. This article addresses the identified gap in the literature and presents a qualitative investigation into the types of disclosures that 16 scholars made online and their reasons for doing so. Results identify wide-ranging personal and professional disclosures. Participants disclosed not only about academia-related issues but also about challenges pertaining to family, mental health, physical health, identity, and relationships. Some scholars disclosed as a way to grapple with challenges they faced; others disclosed tactically, sharing information for political rather than personal reasons. Yet others disclosed as a way to welcome care in their lives. In all instances, though, disclosures were selective, intentional, and approached with foresight.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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