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Record W4361208078 · doi:10.1515/cti-2022-0055

Elements of Country: a First Nations-first approach to chemistry

2023· article· en· W4361208078 on OpenAlexaboutno aff
Anthony F. Masters, Peta Greenfield, Cameron Davison, Janelle G. Evans, Alice Motion, Jennifer H. Barrett, Jakelin Troy, Kate Constantine, Lisa Jackson Pulver

Bibliographic record

VenueChemistry Teacher International · 2023
Typearticle
Languageen
FieldChemistry
TopicHistory and advancements in chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousContext (archaeology)CurriculumTraditional knowledgeSociologyWork (physics)Cultural heritageSpace (punctuation)Environmental ethicsPolitical scienceEngineeringGeographyPedagogyEcologyArchaeologyLawComputer science

Abstract

fetched live from OpenAlex

Abstract Collectively, we have chosen to explore an Australian First Nations-first approach to understanding the chemical elements. We believe that engagement with cultural heritage, ongoing cultures, and the knowledges of this place —the lands on which we work, live, and study—will lead to new ways of understanding the elements and change the way we practice chemistry. The “First Nations first” phrase and approach comes from understanding the unique place that Aboriginal and Torres Strait Islander peoples have in the Australian context. In this paper we explore how a First Nations-first approach could take place in Sydney on Aboriginal lands. This approach is led by Aboriginal people, engages with culture, and is produced with local knowledge holders. So far, the work has entailed two years of meeting, conversing, and sharing space to determine appropriate ways of working together, interrogating the complexities of the ideas, and to refining our approach to the work. To appreciate the significant shift that a First Nations-first approach represents for chemistry, we consider the legacy of the Periodic Table. We share some reflections on how Indigenous knowledges can contribute to an expanded chemistry curriculum through the recognition of productive cultural tension.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.019
GPT teacher head0.269
Teacher spread0.249 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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