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Record W1484246908 · doi:10.5772/19392

Introduction to Bioethics in the 21st Century

2011· book-chapter· en· W1484246908 on OpenAlexaff
Abraham Rudnick, W Kyoko

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsWestern University
Fundersnot available
KeywordsBioethicsPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

Health care is developing rapidly. So are its correlates, such as health care technology, research, education, administration, communication, and more. Such change requires ethical deliberation, as change that is not ethically guided poses unnecessary risks. This may be particularly true in relation to health care, which impacts some of the most central domains of human life. Bioethics addresses issues of health care ethics. It consists of approaches that attempt to resolve moral conflicts, viewed as conflicts among moral values that may each be acceptable in some circumstances but that require prioritizing when combined with other moral values in particular circumstances. Such approaches include the application of theories such as consequentialism, which refers to outcomes (such as happiness); deontology, which refers to duties or intentions (such as the obligation not to lie); virtue ethics, which refers to character features (such as honesty); principlism, which refers to the four principles of upholding autonomy (self-determination), beneficence (best interests), non-maleficence (least harm), and justice (as fairness, for example); and more (Beauchamp & Childress, 2009; Rudnick, 2001; Rudnick, 2002). Bioethics ranges across many areas and its scope is still broadening. Some of its emerging areas address organizational bioethics, global bioethics, and much more. This book focuses on a sample of emerging as well as more established areas of bioethics. The chapters were selected according to various considerations, such as interest of authors. Yet in spite of not being exhaustive, this book illustrates the range and impact of bioethics in the 21st century. As part of that, some of the chapters go beyond fact and theory into some speculation (the chapters with more speculative topics can be found near the end of this book). We think this is necessary for bioethics to be constructive, recognizing that speculation must be checked by common sense as well as by known fact and theory. Indeed this is how much of bioethics proceeds (Rudnick 2007). There are areas of bioethics that are not covered in this book, such as neuroethics, enhancement ethics, ethics of genetics, and more. We cannot touch on most of them here. Still, we would like to highlight neuroethics as a likely paradigm of an emerging area in bioethics. Neuroethics can be defined in part as the ethics of neuroscience (http://en.wikipedia.org/wiki/Neuroethics). More specifically, it can be viewed in part as

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)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.711
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.025
Insufficient payload (model declined to judge)0.0030.006

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 head0.179
GPT teacher head0.456
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations3
Published2011
Admission routes1
Has abstractyes

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