Harbinger of Hope or Commodity Fetishism: "Re-cognizing" Dementia in an Age of Therapeutic Agents
Bibliographic record
Abstract
Choices abound while we await that pharmacogenetic fix that will save each one of us from all that is our individual and collective fate, contingent of course upon panopticon surveillance of our genetic susceptibilities and environmental triggers. The past decade has offered hope to those families facing the impenetrable shroud characterizing cognitive decline and dementia. Sufferers and their physicians have a growing compendium of pharmaceutical therapeutic interventions to attempt to stave off the usual, if not necessarily mindful, course of illness progression. In January 2001, the acetylcholinesterase inhibitors donepezil, rivastigmine, and galantamine were made available in the National Health Service in the United Kingdom, and some are on the formulary of five provinces in Canada. Those provincial pharmacare programs still refusing to provide these therapies free to the elderly cite lack of evidence of efficacy, following Cochrane guidelines based upon systematic review of the best evidence available using randomized controlled trials. Advocates for public funding of the pharmaceutical agents, on the other hand, cite a narratively rich, heart felt host of behavioral and affective symptoms stabilized or boosted by these drugs. And so, the two solitudes are drawn between science and humanity, between the cold guardians of the public purse and the caring humanitarians.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.058 |
| Scholarly communication | 0.009 | 0.023 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.008 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".