Blogging to Counter Epistemic Injustice: Trans disabled digital micro-resistance
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
As part of a larger research project on the intersections between transness, disability, cisgenderism (also called transphobia), and ableism/sanism, this article presents the results of a three-month netnography of blog posts made between 2013 and 2019 by selected Tumblr and off-Tumblr blogs authored by people identifying as both trans and disabled. Mobilizing a theoretical framework that combines trans and disability/crip/Mad theory and the notion of epistemic injustice, we highlight the unique possibilities of community building, connection, identity formation, and micro-practices of resistance in trans disabled digital communities. Trans disabled bloggers counter epistemic injustice by speaking back, reclaiming space, and responding to the cisgenderist and ableist/sanist micro-aggressions they experience in their daily lives. This exploration of trans disabled bloggers' micro-activism is divided into four parts. After reviewing the literature in the emerging field of trans disability studies in the first part, the second and third parts present our theoretical and methodological frameworks. Findings are presented and discussed in the three subsections of the fourth part, which delves deeper into our typology of three interrelated genres of trans disabled blog posts: informational, testimonial, and activist. As their names suggest, these genres aim respectively to: 1) inform other trans disabled internet users of identificatory possibilities; 2) testify about bloggers' lived experiences; and 3) advocate for trans disabled people through appeals to users both within and outside trans and disabled communities.
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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 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