Bibliographic record
Abstract
This study is a critical discourse analysis of the Mini-Mental State Exam (MMSE), an assessment tool used to screen older adults for cognitive impairment worldwide. In it, I deconstruct and unmap two unofficial versions of the MMSE to reveal how its discursive practices are grounded in ageism, ableism, sanism, and other forms of oppression. I challenge the MMSE’s status as a neutral container for knowledge by uncovering how it actively defines “cognitive impairment” and “cognitively impaired” identity formation through epistemic violence. I discuss five key issues: consent, scoring, claims-making, voice, and copyright. Lastly, I reflect on how hegemonic discourses about “dementia” keep older adults and people with cognitive impairments in their social place while maintaining the multi-billion dollar “care” industry. This study highlights how social workers are implicated in injustices against older adults that are often hidden. I hope it will be the impetus for transformative change in this field. Keywords: Mini-Mental State Exam, short cognitive test, discourse analysis, unmapping, cognitive impairment, older adults, gerontology, anti-oppressive practice
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".