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Record W7035913661

ACCOUNTS OF VIETNAMESENESS: MAPPING VIETNAMESE BUDDHISM(S) IN MONTREAL

2023· dissertation· en· W7035913661 on OpenAlexaffabout

Bibliographic record

VenueMacSphere (McMaster University) · 2023
Typedissertation
Languageen
FieldNeuroscience
TopicEmbodied and Extended Cognition
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDisenchantmentVietnameseEveryday lifeBuddhismReligious lifeImmigrationAsian studies
DOInot available

Abstract

fetched live from OpenAlex

This thesis is a study of religion in movement through retellings of stories from members of the Vietnamese-Canadian immigrant community in Montreal, Québec. It aims to demonstrate that religion, specifically Buddhism, plays an important role in processes of homemaking. The thesis maps Vietnamese Buddhism as a complex system of shifting beliefs and practices, highly contingent on its encounters with different environments and people. It aims to show that the tradition is strongly anchored in members of the community’s everyday life given that it is tightly intertwined with cultural ways to interact, eat, care, and treat their family members, alive and dead. This thesis, following North American Religions scholars, aims to challenge the assumption that the modern world, due to its post-Enlightenment disenchantment with the superstitious in the move toward the rational and scientific, has been “secularized,” that is, emptied of religion, which has declined and become privatized. It argues that religion still has much to do with the way everyday life is lived. The research thus takes up a “lived religion” approach to enquire into the ordinary religious subject’s everyday practices in new, often non- religious, and profane spaces, rather than the explicit and exclusive religious life of the unambiguously religious individual. It aims to demonstrate that studying religion constitutes a generative avenue to understanding societies today.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.026
GPT teacher head0.235
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designOther design
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

Citations0
Published2023
Admission routes2
Has abstractyes

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