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Record W2783519863 · doi:10.5539/ach.v10n1p71

Multiculturalism in the Local Wisdom of Bajo Tribe

2018· article· en· W2783519863 on OpenAlexvenueno aff
La Ode Ali Basri

Bibliographic record

VenueAsian Culture and History · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMulticultural Education and Local Wisdom
Canadian institutionsnot available
Fundersnot available
KeywordsTribeMulticulturalismAction (physics)SociologyPsychologyAnthropologyPedagogy

Abstract

fetched live from OpenAlex

This research reveals multiculturalism contained in the oral tradition of the Bajo tribe. The results showed that multiculturalism in Bajo tradition is as follows; 1) ethical philosophy of the Bajosnamely tahangdiri (self-control) and ngatonang diri (self-awareness). Tahang diri is the ethical concept of behaving of Bajo tribe that in their life, they must refrain from misbehavior. Ngatonang diri implies that every individual should be aware of all the weaknesses and the strengths they belong. Bajoprincipally are ordinary people who cannot survive without the helpfrom other people, the sea and the Ruler of the sea; 2) the tradition of pamali (taboos), for instance pamali making the neighbors annoy by throwing the clamshells into their boat and throwing the sand in their yard and pamali killing the animals such as pig, jonga (deer) and other land animals that descend into the sea; 3) the problem solving tradition of Bajo through the arbitration system in which if there is a conflict among the people, there should be third person (mediator) to take an action in solving the problem.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.007
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.307
Teacher spread0.281 · 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 designQualitative
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

Citations9
Published2018
Admission routes1
Has abstractyes

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