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Record W4385476107 · doi:10.1093/geront/gnad105

A Genealogy of the <i>Life History Album</i> (1884): Gerontology, Genre, and Health Across the Life Span

2023· article· en· W4385476107 on OpenAlexaff
Suzanne Bailey

Bibliographic record

VenueThe Gerontologist · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsTrent University
Fundersnot available
KeywordsSubject (documents)HumanismContentmentArgument (complex analysis)Reading (process)HistoryLiteratureGerontologyPsychologyMedicineArtPhilosophyLinguisticsLibrary scienceSocial psychology

Abstract

fetched live from OpenAlex

This paper demonstrates what emerges when we undertake a literary reading of a medical text, examining its form and structure as a text. The study of what appears to be a singular publication reveals instead an under-examined moment in medical history that anticipates contemporary health investigations in modern medicine, while reflecting the limitations of medical and gerontological knowledge in the 1880s. I demonstrate this argument by conducting a Foucauldian archeology of the text, with attention to authorship and the concept of textual genre. My primary text is the Life History Album (1884), which I link to a related endeavor, G. M. Humphry's Old Age (1889), a little-known publication that contains medical observations on the resiliency of aging bodies and anticipates ideas associated with early twentieth-century geriatrics. My investigation brings new attention to the work of Dr. Frederick Akbar Mahomed, a pioneer in the study of hypertension, whose story is part of the genealogy of the text. Inviting its creator to keep records of health throughout the life span, the Life History Album anticipates a new kind of modern subject, who participates in co-creating his or her medical and life health history, whereas Humphry's Old Age, which draws on similar methods, is humanistic, includes literary references, and allows for contentment in older age.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.343
GPT teacher head0.399
Teacher spread0.056 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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