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Record W2950753864 · doi:10.1177/2514848619855367

Schrödinger’s placenta: Determining placentas as not/waste

2019· article· en· W2950753864 on OpenAlexafffundabout
Rebecca Scott Yoshizawa, Myra J. Hird

Bibliographic record

VenueEnvironment and Planning E Nature and Space · 2019
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsQueen's UniversityKwantlen Polytechnic University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPraxisPlacentaOntologyHuman placentaHuman healthIndeterminacy (philosophy)SociologyEpistemologyEngineering ethicsBiologyMedicineEnvironmental healthPhilosophyFetusPregnancyEngineeringGenetics

Abstract

fetched live from OpenAlex

An estimated 50 million kilograms of human placental material is produced worldwide every year. In countries such as Canada, human placentas are utilized in scientific research concerned with fetal and women’s health, immunology, and cancer, to name a few. Through an empirical study involving interviews with placenta scientists and observations of placental science research laboratories and meetings, this article examines the material and discursive processes through which placentas are rendered materially and ethically available for scientific study. We argue that these processes involve a critical shift in placenta ontology such that placentas exist as waste and not-waste, an indeterminacy that is resolved in a four-phase praxis. The praxis ultimately makes placentas not only available, but also monetarily and morally ‘free of charge’ for scientific purposes. Our analysis reveals that the purported waste-ness of placentas potentiates their amenability to scientific experimentation, and is foundational to scientists’ claims about their moral relationship with broader publics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.899

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 integrity0.0000.001
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 head0.014
GPT teacher head0.291
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2019
Admission routes3
Has abstractyes

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