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Record W4399853719 · doi:10.4324/9781003224662-5

Maude & Me 1

2024· book-chapter· en· W4399853719 on OpenAlexaboutno aff
Annmarie Adams

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMaterials science

Abstract

fetched live from OpenAlex

I’m a sixty-four-year-old architectural historian. I am writing a spatial biography of a relatively famous female physician, Maude Abbott, who died in 1940 at the age of seventy-two. In this project, I engage the history of architecture and its tools by telling a life story through ten spaces Abbott occupied, rather than the barriers she faced. I dig deeply at particular events and locations, looking for evidence of Abbott’s biographical traces. This methodology, somewhat inspired by archaeology, emphasizes social and physical settings. It de-stabilizes the accounts of her life by others, especially male doctor-biographers. The sites I have chosen are a series of multi-dimensional snapshots that showcase relations between the personal and the social, the private and the public Maude Abbott. My own life unfolds in the sources I study. I regularly traverse the Montreal spaces that Abbott occupied. I teach in classrooms that kept her out. Her beloved medical specimens are now a museum, which I often visit. I twice gave birth in a hospital she knew well. I walk the streets she walked. Maude & me.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.008

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 head0.026
GPT teacher head0.222
Teacher spread0.196 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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