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Record W2292444262 · doi:10.1162/posc_a_00225

Emerging Science, Emerging Democracy: Stem Cell Research and Policy in Taiwan

2016· article· en· W2292444262 on OpenAlexaff
Jennifer A. Liu

Bibliographic record

VenuePerspectives on Science · 2016
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDemocracyStem cellPolitical scienceEnvironmental ethicsSociologyBiologyPhilosophyCell biologyPoliticsLaw

Abstract

fetched live from OpenAlex

Science policymakers in newly democratic Taiwan grapple with a central tension of how to construct policies that both conform to international standards and properly represent Taiwan’s people. Based on more than sixteen months of ethnographic research, over a hundred interviews, and archival data, I examine how stem cell research-related policymaking was assembled in Taiwan. I pay particular attention to the intersections of global and local, and to articulations of democracy, sovereignty, and identity as they relate to stem cell research governance. While much has been written on science and democracy in established democratic societies, relatively little has addressed the relationship between emergent democracies and emergent sciences. I suggest that studies in Taiwan as it transitions from technocratic to democratic authority help to make visible the diverse logics and multiple considerations that shape both biotech and its governance in an emergent science democracy.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.008
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.420
Teacher spread0.368 · 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.

Study designQualitative
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

Citations3
Published2016
Admission routes1
Has abstractyes

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