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Record W3177824567 · doi:10.5539/ach.v13n1p1

The Relationship between the Moso Settlements and the Mani Lumps

2021· article· en· W3177824567 on OpenAlexvenueno aff
Hiromu ITO, Wei Yu

Bibliographic record

VenueAsian Culture and History · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
FundersFogarty International CenterJapan Society for the Promotion of Science
KeywordsWorshipHuman settlementTourismSettlement (finance)GeographySociologyArchaeologyPolitical scienceLawBusiness

Abstract

fetched live from OpenAlex

The Moso and Nasi minority groups inhabit the area around Lugu Lake, which also includes mani lumps that are associated with nature worship. The setting of the mani lumps differs from one village to another. This study aims to examine the relationship between the characteristics of the Moso settlements and settings of the mani lumps in addition to the functions of each mani lump. The results show that the function of the mani lumps may vary depending on the topography of the settlement, the adjacency between settlements, and the religious facilities in place. Many mani lumps have a view of the Goddess Mountain and may have been established according to the villages’ characteristics based on their inherited nature worship beliefs. Lugu Lake is currently undergoing tourism development because of its landscape, and cultural tourism activities based on nature worship with the mani lumps as the centerpiece are expected to be developed.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.277
Teacher spread0.238 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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