MétaCan
Menu
← Back to cohort
Record W2478730017 · doi:10.1017/cbo9781139167406.004

Clarifying and Revising the Criteria

2008· book-chapter· en· W2478730017 on OpenAlexaff
C. G. Prado

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook-chapter
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsQueen's University
Fundersnot available
KeywordsEpistemologyPsychologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The criteria articulated in the previous chapter raise a number of questions, some of which have to do with the criteria themselves, and some with broader issues. The first question that needs to be dealt with is precisely what the criteria apply to . Specifically, I have been speaking of PS1, SS2, AS3, and RE4, that is, preemptive, surcease, and assisted suicide at the three stages described in Chapter 2, and requested euthanasia at the fourth stage. More generally, I have been speaking of choosing to die and elective death. To deal best with the question of exactly what the criteria apply to, I need to speak of suicide in particular, meaning PS1, SS2, and AS3, and exclude RE4 except where explicitly mentioned. Since the criteria are offered as a way to establish when suicide is rational, it may seem odd to raise the question of the nature of the object of their application, but as mentioned before, there is currently a significant amount of confusion that glosses the differences among suicide, assisted suicide, and euthanasia. It is important, then, to make as clear as possible what it is that is to be assessed as rational or otherwise, and so as possibly morally permissible. The Oxford Companion to Philosophy has it that “the most conventional definition of ‘suicide’ is intentionally caused self destruction.” Difficulties begin with how “self-destruction” is understood.

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)0.077
metaresearch head score (Gemma)0.191
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.407

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.191
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.007
Science and technology studies0.0090.021
Scholarly communication0.0210.027
Open science0.0070.009
Research integrity0.0100.024
Insufficient payload (model declined to judge)0.0090.004

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 head0.134
GPT teacher head0.381
Teacher spread0.247 · 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 designTheoretical or conceptual
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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooks→Same topicEthics in medical practice→French-language works237,207→