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Organ Transplantation in Russia: An Anthropological Perspective

2022· article· en· W4206224562 on OpenAlexvenueno aff
Dmitry Mikhel

Bibliographic record

VenueAnthropologica · 2022
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsTransplantationPerspective (graphical)Context (archaeology)Object (grammar)SociologyOrgan transplantationAnthropologyOrgan donationEnvironmental ethicsSocial scienceEngineering ethicsEpistemologyMedicineHistoryComputer science

Abstract

fetched live from OpenAlex

This article offers an anthropological perspective on organ transplantation in Russia. The author employs approaches and principles of medical anthropology and ontological turn in anthropology and attempts to present a novel human-object history of organ transplantation. This research focuses primarily on human collectives, such as medical communities and the rest of society, but also on certain objects, including donor organs and the infrastructure created by the technology. The article discusses the following questions: How does transplantation technology transform the medical community? How is it built into the social and cultural context? How is it perceived by the rest of society? How do some doctors try to adapt this technology to the traditional values of Russian society? This research was conducted at two large Russian organ transplantation centers. The analyzed materials include anthropological and medical publications, and mass media sources.

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 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 score0.510
Threshold uncertainty score0.988

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.024
GPT teacher head0.349
Teacher spread0.325 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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