“Enough has yet to be said”: Dialoguing neoliberal ideology, pedagogy, and subjectivity in science education
Bibliographic record
Abstract
This paper endeavours to discuss further the pressing issue of neoliberalism (along with the accompanying realities of consumerism and globalization) and its pervasiveness in the field of science education. A number of recently published science education journal issues (CSSE, JRST and soon to be Science & Education) have significantly opened and exposed issues in science education concerning neoliberalism and consumerism in the context of globalization and global capitalism. This significant shift in the science education literature has brought forth diverse voices about/against neoliberalism along with different approaches to research in the field of science education. The goal of this paper is to contribute to this discourse by joining post-structural and pedagogical voices for change in science education. We discuss specifically the usefulness of the post-structural subject, some aspects of the field of science education, and the power of pedagogical approaches concerning neoliberalism in the form of dialogue. The authors, two doctoral students from Canada and Greece, bring forth both divergent and convergent perspectives and in doing so create new understandings between themselves regarding the relationships between neoliberalism, science education, pedagogy and post-structuralism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.106 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".