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Assessing Twenty-Two Life-Changing Events of Emily Howard Jennings Stowe with a Unique Narrative Research Process

2023· preprint· en· W4389323007 on OpenAlexaffabout
Carol Nash

Bibliographic record

VenuePreprints.org · 2023
Typepreprint
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativeOrder (exchange)Interpretation (philosophy)Principal (computer security)HistoryPoint (geometry)PsychologySociologyLiteratureArtComputer scienceBusiness

Abstract

fetched live from OpenAlex

Emily Howard Jennings Stowe is acclaimed as Canada’s first female school principal, physician to practice medicine, and a founding Canadian suffragette. Yet, relatively little has been investi-gated regarding the life-changing events permitting her to pioneer in these chosen fields. To reveal relationships among the life-changing events in Emily Stowe’s life, a unique narrative research process is engaged to take Stowe’s story and develop it into a particular point of view based on responses to questions posed regarding her life, ranging from those most objective and specific to those that are subjective and more general. This is accomplished by following a prescribed order of question-asking: when, where, who, what, how, and why. The aim is to facilitate a comparison and interpretation of the connections regarding twenty-two of her life-changing events. Four dis-tinct aspects of her life are noted: personal, teacher, physician, and suffragette. It is found that much of Stowe’s success originated from her family’s Establishment connections, her studious intellectual ability, and her decision to obtain her medical education in the United States. There were notable periods in her life that might have ended her career. However, the aforementioned protective features of her status permitted the successful withstanding of these difficulties.

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)0.007
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0190.010
Scholarly communication0.0070.004
Open science0.0020.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.287
GPT teacher head0.465
Teacher spread0.179 · 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 designQualitative
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 routes2
Has abstractyes

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Same venuePreprints.orgSame topicCanadian Identity and HistoryFrench-language works237,207