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Record W2475007206

Heart and Soul: Women, heal thyselves

2002· article· en· W2475007206 on OpenAlexvenueaboutno aff
Heather Kent

Bibliographic record

VenueCanadian Medical Association Journal · 2002
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)MedicineScholarshipLawHistoryPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This month Jerilynn Prior, a Vancouver endocrinologist, will give UBC's Distinguished Medical Research Lecture. For Prior, 59, the occasion is a profound marker of how far women have come in medicine. “I've earned a reputation as a scientist,” she says, “and [today] people are less quick to judge someone negatively just because she is a woman.” Her research has broken new ground in areas such as the link between osteoporosis and menopause, and prepubescent girls' eating attitudes and bone density. And she has also launched the Centre for Menstrual Cycle and Ovulation Research, which will interpret scientific knowledge of the menstrual cycle and ovulation in a woman-centred context. “Most of the knowledge we have was created in an era when women were thought to be disadvantaged by biology,” she says. Prior grew up in Alaska. A missionary's daughter, she earned a scholarship to study nursing, but she decided to pursue a medical career. She graduated from Boston University in 1969, and quickly learned that private hospitals “asked for insurance first and then decided if the person was living or dying. It became clear that given my conscience I wouldn't be able to turn patients down because they couldn't pay.” This conflict led to her move to Canada, where she became chief resident in medicine at the Vancouver Hospital. She specialized in endocrinology — “it was less focused on diseases than many specialties” — and pressed ahead on another front, too. Because she is conscientiously opposed to military spending and war and believes that the Charter grants her freedom of conscience and religion, she refused to pay the portion of her income tax that would be devoted to defence spending after she became a Canadian citizen in 1984. Instead, she paid this portion of her taxes owing to the Peace Trust Fund. She was eventually ordered to pay, and her appeal of that decision, which eventually reached the Supreme Court, was unsuccessful. When it comes to medicine, her drive probably comes from her different perspective on women's reproduction. “Early on, I began to see that ovulation was an important aspect that had been virtually ignored.” Prior also became involved in research that challenged another dogma — that menopause causes osteoporosis. “I want to know what is really going on and not just [be affected by] a cultural prejudice,” she says. She attributes the cultural prejudice surrounding menopause to the traditional positioning of women's reproduction in a surgical specialty instead of a medical one. “I would like to totally rewrite the medical school curriculum on this — they are still learning that dropping estrogen levels causes perimenopausal misery.” Prior says one of the next frontiers in women's health will be crossed by sociocultural experts who can “talk a language that is understood by the biologists. At the moment there is a big rift, and unfortunately I sit right in the middle of it. I've worked long and hard to get collaborators from these other fields, and it has been almost as hard a struggle as it has been to make my way in the medical world.” — Heather Kent, Vancouver

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)0.003
metaresearch head score (Gemma)0.007
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.009
Scholarly communication0.0090.008
Open science0.0010.007
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0230.009

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 head0.032
GPT teacher head0.339
Teacher spread0.307 · 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
GenreCommentary

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
Published2002
Admission routes2
Has abstractyes

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