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Record W4206385388 · doi:10.1002/sce.21700

Humanistic science education: The history of science and other relevant contexts

2022· article· en· W4206385388 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHumanismScience educationScience, technology, society and environment educationSocial science educationContext (archaeology)Graduation (instrument)Nature of ScienceHistory of scienceOutline of social scienceEngineering ethicsSociologyMathematics educationPhilosophy of scienceSocial sciencePedagogyEpistemologyPsychologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Abstract This article offers a retrospective synopsis of 70 years of development of a humanistic approach to science education. Instruction using the history of science, for example, provides a rich context for students to learn not only canonical science content on a need‐to‐know basis, but also content from the other domains of humanistic science education, including: the nature of science and scientists, cultural studies, and the multifarious interplay between science/scientists and society. The synopsis leads to the conclusion that instructional materials and student assessment tools developed earlier for teaching the history of science are relevant today. Science–technology–society–environment and socioscientific issues, two of the present six domains of humanistic school science, are given special attention. An example of their teaching materials is described, which illustrates in detail how to organize lessons or units particularly suited for the substantial majority of high school students who would not enroll in any current science classes if not required for graduation. Trends suggested for the future are based on shifts in current global economics.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.016
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0090.042
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.399
Teacher spread0.335 · 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