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Record W2908078030

The feminization of HPV: How science, politics, economics and gender norms shaped U.S. HPV vaccine implementation

2017· article· en· W2908078030 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublisher · 2017
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsFeminization (sociology)HPV infectionPublic healthMedicineGenital wartsHPV vaccinesGynecologyCervical cancerPolitical scienceFamily medicineGender studiesCancerSociologyPathologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Human papillomavirus (HPV) can cause a number of anogenital cancers (i.e., cervical, penile, anal, vaginal, vulvar) and genital warts. A decade ago, the HPV vaccine was approved, and has been shown to be a public health achievement that can reduce the morbidity and mortality for HPV-associated diseases. Yet, the mistaken over-identification of HPV as a female-specific disease has resulted in the feminization of HPV and HPV vaccines. In this critical review, we trace the evolution of the intersection of science, politics, economics and gender norms during the original HPV vaccine approval, marketing era, and implementation. Given the focus on cervical cancer screening, women were identified as bearing the burden of HPV infection and its related illnesses, and the group responsible for prevention. We also describe the consequences of the feminization of HPV, which has resulted primarily in reduced protection from HPV-related illnesses for males. We propose a multilevel approach to normalizing HPV vaccines as an important aspect of overall health for both genders. This process must engage multiple stakeholders, including providers, parents, patients, professional organizations, public health agencies, policymakers, researchers, and community-based organizations.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.367
Teacher spread0.315 · 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