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Record W2039232601 · doi:10.1111/0591-2385.00286

Education for the Heart and Mind: Feminist Pedagogy and the Religion and Science Curriculum

2000· article· en· W2039232601 on OpenAlexaff
Joyce Nyhof‐Young

Bibliographic record

VenueZygon® · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsPraxisFeminist pedagogyCurriculumFeminist philosophySociologyPedagogyFeminist epistemologyEpistemologyFeminismGender studiesPhilosophy

Abstract

fetched live from OpenAlex

Feminist educators and theorists are stretching the boundaries of what it means to do religion and science. They are also expanding the theoretical and practical frameworks through which we might present curricula in thosefields. In this paper, I reflect on the implications of feminist pedagogies for the interdisciplinary field of religion and science. I begin with a brief discussion of feminist approaches to education and the nature of the feminist classroom as a setting for action. Next, I present some theoretical and practical issues to consider when developing a feminist praxis and an antisexist curriculum. This leads into a discussion of the role of language and critical reflection in the religion and science classroom, the risks associated with reflective discourse, and considerations in the use of ‘feminist’ teaching tools such as small group work, journals, and portfolio assessment. Iconclude with a reflection on how feminist pedagogy promotes an epistemology that speaks to the hearts and minds of participants in the dialogue of religion and science.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.021
Scholarly communication0.0050.005
Open science0.0010.005
Research integrity0.0020.004
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 head0.014
GPT teacher head0.368
Teacher spread0.355 · 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 designTheoretical or conceptual
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

Citations9
Published2000
Admission routes1
Has abstractyes

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