Fact Construction and Categorization in Assessment: Cultivating Epistemic Justice and Resistance in Social Work Assessment
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
When an individual’s experience is discredited and their views silenced in conversation, epistemic injustice ensues, resulting in an ontological attack on the individual’s human dignity. I examine how social workers claim to know and construct the facts of clients’ experiences, subsequently categorizing them in accordance with professional and institutional knowledge. These constructs may differ from the clients’ own experiences, perpetuating epistemic injustice. Elaborating a process of fact construction and categorization in two case examples, I interrogate the inevitable workings of power at multiple levels during assessment. I argue categorization as a site of epistemic injustice serving three functions: permitting dominant discourses to be taken-for-granted and to legitimize professional actions, framing interactional tasks to align with professional and institutional agendas, and enticing clients and workers with activity-bound accountability, obligation, and entitlement. This analysis invites social workers to reflect critically on how to resist epistemic and social injustice in everyday assessment.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 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