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Contribution for the teaching of natural sciences: Mapuche and school knowledge

2014· article· en· W1975726848 on OpenAlexaff
Segundo Quintriqueo M., Daniel Quilaqueo Rapimán, Héctor Torres Cuevas

Bibliographic record

VenueEducação e Pesquisa · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Education, Indigenous Social Dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsContext (archaeology)Natural (archaeology)SociologyCultural knowledgeRelation (database)PoliticsEpistemologyPedagogyPsychologySocial scienceGeographyPolitical scienceArchaeologyComputer science

Abstract

fetched live from OpenAlex

Within the context of Mapuche families and communities, this paper focuses on the relationship between knowledge and educational methods in teaching the natural sciences. It aims to identify educational methods that have been forged and re-forged in connection with the social, cultural, political, economical and spiritual development experienced by Mapuche communities. Our educational research methodology is based on a qualitative approach in order to unveil the subjective and inter-subjective dimensions that characterize the subjects' educational knowledge in their life context. Our fieldwork has been carried out from a sample of interviews conducted with Mapuche wise men (sabios) living in the Araucanía. The results of the study are divided in four categories: 1) Relationship towards the natural environment; 2) Knowledge regarding living beings; 3) Küyen cycle (phases of the Moon); and finally, 4) Healthy lifestyle. The collected data have allowed us to link different contents (conceptual, practical and attitudinal) underlying the proper Mapuche educational methods to underline their rationalities with reference to core knowledge. Thus, we want to make a case for an epistemological basis substantiating the teaching of natural sciences in relation to Mapuche knowledge. This will allow us to contextualize natural science teaching within the framework of an intercultural educational approach. By doing so, we aim to establish an intellectual dialogue in a context of interethnic and intercultural relationships.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.346
Teacher spread0.330 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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