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Record W2991976865 · doi:10.1088/1361-6552/ab537d

The giant, the wintermaker, and the hunter: contextual ethnoastronomy towards cultivating empathy

2019· article· en· W2991976865 on OpenAlexfundno aff
Richard P. Hechter

Bibliographic record

VenuePhysics Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
FundersUniversity of Manitoba
KeywordsEmpathyScience educationPsychologyMathematics educationPedagogySociologySocial psychology

Abstract

fetched live from OpenAlex

Abstract ‘It is the belt!’ This is how middle school teachers in a science teaching professional development program rationalized why they believe Orion is the most recognizable of all constellations in the night sky. It was from this foundation that we chose Orion to be the focus of a four-phase ethnoastronomy-based project reported here. Ethnoastronomy, within this context, can be described as the study of myths as bearers of cultural knowledge from oral traditional societies (Lankford 2007 Reachable Stars: Patterns in the Ethnoastronomy of Eastern North America (Tuscaloosa, AL: University of Alabama Press)). After identifying the stars comprising the ‘belt’, and the greater asterism through the singular and oversimplified lens of the Greek mythology that dominates our astronomy curricular learning objectives, we explored deeper through Ojibwe, Arab, and Jewish perspectives as these cultures and religions were represented in our group. The purpose of this paper is to share insights emanating from emergent critical questions generated in our professional development program regarding where, how, and why we should introduce traditional cultural knowledge that complements Western skylore into our classrooms towards helping to cultivate empathy for others in our community.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.364
Teacher spread0.334 · 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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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