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Record W3127467720 · doi:10.1080/11287462.2021.1879462

Exploring values among three cultures from a global bioethics perspective

2021· article· en· W3127467720 on OpenAlexaffabout
Kristen Jones-Bonofiglio, Claudia R. Sotomayor

Bibliographic record

VenueGlobal Bioethics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsAssociated Medical ServicesLakehead University
Fundersnot available
KeywordsBioethicsIndigenousEnvironmental ethicsPluralism (philosophy)SociologyHumanityXhosaDeclarationCultural diversityHealth careHuman rightsDeclaration of HelsinkiSocial sciencePolitical scienceAnthropologyMedicineLawInformed consentEpistemology

Abstract

fetched live from OpenAlex

The United Nations Educational, Scientific and Cultural Organisation's (UNESCO) Declaration on Bioethics and Human Rights refers to the importance of cultural diversity and pluralism in ethical discourse and care of humanity. The aim of this meta-narrative review is to identify indigenous ethical values pertaining to the Ojibway (Canada), Xhosa (South Africa), and Mayan (Mexico and Central American) cultures from peer-reviewed sources and cultural review, and to ascertain if there are shared commonalities. Three main themes were identified, namely illness, healing, and health care choices. Illness was described with a more complex and dynamic picture than from the western view, as illness is not considered to be one dimensional. Healing needs to take place on various levels in order to restore a state of equilibrium between the different spheres. Health care choices were also considered from a multi-level perspective. In all three of the indigenous cultures explored, good decision-making is seen to have occurred when choices are informed by commitments to one's moral and ethical responsibilities towards the community, nature, and the spirit world.

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)0.026
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0050.014
Scholarly communication0.0100.010
Open science0.0010.007
Research integrity0.0020.003
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 head0.402
GPT teacher head0.541
Teacher spread0.139 · 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
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

Citations7
Published2021
Admission routes2
Has abstractyes

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