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Record W3128982681 · doi:10.1186/s12052-020-00141-9

Biology teachers’ conceptions of Humankind Origin across secular and religious countries: an international comparison

2021· article· en· W3128982681 on OpenAlexfundno aff
Heslley Machado Silva, Alandeon W. Oliveira, Gabriela Varela Belloso, Martín Andrés Díaz, Graça Simões de Carvalho

Bibliographic record

VenueEvolution Education and Outreach · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicEvolution and Science Education
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversidade do MinhoInternational Council for Canadian Studies
KeywordsCreationismReligiosityIdeologyEnvironmental ethicsLatin AmericansSociologySocial sciencePolitical scienceEpistemologyLawPoliticsPhilosophy

Abstract

fetched live from OpenAlex

Abstract Striving toward a better understanding of how the global spread of creationist ideology may impact biology teachers and teaching worldwide, this study comparatively examines how biology teachers from three Latin American countries (Argentina, Brazil, and Uruguay) conceive the origin of humankind. It is reported that teachers from Uruguay (the most secular country) and Argentina (a country with intermediate religiosity) more frequently associated humankind origin with scientific terms Evolution, Natural selection, and Australopithecus. In contrast, Brazilian teachers stood out as those most frequently associating humankind’s origin to the religious term “God” alongside scientific terms. This study underscores the importance of the interplay of social factors (societal religiosity) and psychological factors (e.g., personal commitment) when considering the impact of teacher exposure to creationist ideology. It also highlights the need for biology teachers (particularly those in more religious countries) to undergo professional development.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.040
GPT teacher head0.368
Teacher spread0.327 · 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 designObservational
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

Citations17
Published2021
Admission routes1
Has abstractyes

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