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Record W337286892 · doi:10.1093/jhmas/jrl058

Jesse F. Ballenger. Self, Senility, and Alzheimer's Disease in Modern America: A History. Baltimore, Maryland, The Johns Hopkins University Press, 2006. xvii, 236 pp. $43

2007· article· en· W337286892 on OpenAlexaffabout
Pia Kontos

Bibliographic record

VenueJournal of the History of Medicine and Allied Sciences · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsGerontologyHistoryLibrary scienceMedicine

Abstract

fetched live from OpenAlex

Alzheimer's disease is considered to be the most dreaded condition that faces the aging population in the twenty-first century. In Self, Senility, and Alzheimer's Disease in Modern America, Jesse F. Ballenger locates the dread surrounding dementia in its historical context, examining its origins, its connection to broader social and cultural developments in America, and the way in which it has shaped knowledge about dementia, health policy, and the experience of caregivers and persons with dementia. Chapter one traces the emergence of the negative stereotype of senility in the late nineteenth century to the material and ideological forces of an expanding market economy and the broad democratization of American society. In the context of industrial production, the market revolution, mass consumption, and the triumph of a liberal social order, selfhood shifted from an ascribed status to being intentionally constructed by the individual. With these changes, selfhood became more dependent upon the ability of individuals to sustain a coherent self-narrative—with the result that the impairment of this ability by dementia now threatened one's fundamental status as a human being. As Ballenger so eloquently states, “senility haunts the landscape of the self-made man” (9).

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0010.003
Scholarly communication0.0010.005
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.008

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.

Opus teacher head0.050
GPT teacher head0.236
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2007
Admission routes2
Has abstractyes

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