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Record W7020133884

Lactation Newsmakers Column: An interview with Penny Van Esterik, MA, PHD

2018· other· en· W7020133884 on OpenAlexaboutno aff

Bibliographic record

VenueNC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) · 2018
Typeother
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsBreastfeedingScholarshipNature versus nurtureAllianceContext (archaeology)PopulationFeminismPolitics
DOInot available

Abstract

fetched live from OpenAlex

It is my great pleasure to interview Penny Van Esterik, who is truly a “foremother” in our field. Penny is an anthropologist, and it is that background that defines her approach to scholarship and practice. She was educated in both the United States and Canada and is Professor Emerita in the Department of Anthropology at York University in Toronto where she worked for 30 years. She has authored many books, chapters, and articles and continues to be a sought-after speaker. This interview was inspired by her keynote address at the 2018 Breastfeeding and Feminism International Conference, where she spoke about themes from her recently published book, The Dance of Nurture: Negotiating Infant Feeding (Van Esterik & O’Connor, 2017). Her 1989 book, Beyond the Breast-Bottle Controversy (Van Esterik, 1989), was widely read and helped us better position breastfeeding within the context of both food systems and gender. She has consulted with, among others, UNICEF, Wellstart Lactation Management, Canadian International Development Agency, the Population Council, and the World Alliance for Breastfeeding Action (WABA). Her writing considers breastfeeding and nurture within many different contexts including culture, gender, work, food systems, HIV/AIDS, body politics, environmental sustainability, and human rights. Her work illustrates that the personal is political and the political, personal, reminding us to align our policies and practices to reflect the real stories and experiences of real people in their real contexts.

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)0.005
metaresearch head score (Gemma)0.017
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: Other · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0170.004
Scholarly communication0.0110.010
Open science0.0020.004
Research integrity0.0060.020
Insufficient payload (model declined to judge)0.0160.006

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 head0.260
Teacher spread0.228 · 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
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
Published2018
Admission routes1
Has abstractyes

Explore more

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