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Record W4281750958 · doi:10.28984/ct.v3i1.388

Buddhism and Soteriology

2022· article· en· W4281750958 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCon Texte · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBuddhismSoteriologyGautama BuddhaConversationFocus (optics)MetaphysicsPhilosophyEpistemologyTheologyLinguistics

Abstract

fetched live from OpenAlex

This paper argues that research in Buddhism must have a soteriological focus. To demonstrate this, an overview of the Cūḷamālunkya Sutta (MN 63) is presented. This sutta consists of a conversation between the Buddha and one of his students, and it reveals that Buddhism’s topics of inquiry must address how one can be free from suffering. The implication of this conversation – the soteriological focus – seems to suggest that Buddhist research excludes topics in metaphysics, such as addressing the nature of the universe (if it has a beginning or an end, if it is finite or infinite, and so forth), or the nature of the self. Soteriology seems to suggest that ethics is the only focus of research in Buddhism; that is, to know how to be free from suffering, one must study how one should live and conduct oneself. Though this appears to be the case, this paper will show that research in Buddhism is not limited in this manner. Instead of excluding metaphysical research entirely, Buddhism instead excludes research that is done for its own sake; topics must therefore be researched for the sake of soteriology. Thus, the research implication of the Cūḷamālunkya Sutta is not that certain topics are unable to be researched, but rather that a qualification of soteriology is attached to topics of research.

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.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.085
GPT teacher head0.497
Teacher spread0.412 · 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