Anti-capitalist/Pro-communitarian Science & Technology Education
Bibliographic record
Abstract
Many of us live in a hyper-economized world, in which personal identities and routine practices aresignificantly oriented towards production and consumption of for-profit goods and services. Extremeconsumerism appears to be strongly associated with many personal, social and environmental problems. It isapparent that professional science and science education help facilitate this problematic hypereconomization.Briefly, science education tends to emphasize generation of knowledge producers, includingengineers, scientists and other symbolic analyzers — who, in turn, develop and manage mechanisms ofproduction of goods and services. At the same time, fields of professional science (e.g., via data-mining andmarketing) and science education (e.g., via guided discovery inquiries) orient citizens towards habits ofunquestioning and enthusiastic consumption of goods and services. Central to this system of problematic forprofithyper-consumerism appear to be epistemological and ethical considerations. Science, for example,often is seen — largely misleadingly — as a very systematic and decontextualized process generating highlyeffective and unproblematic products/services that can contribute greatly to individuals’ wellbeing. In thispaper, we counter these epistemological and ideological stances through argumentative support — partlythrough summaries of two educational case studies (Science and the City and STEPWISE) — forcommunitarianism. Under this philosophy, knowledge is seen as historically and temporally complex, perhapsleading us to a communalist (if not altruistic) ethical position with regards to the wellbeing of individuals,societies and environments. Ramifications of these positions for science education may include: Equity,Diversity, Holism, Breadth, Depth, Empowerment, Self-determination, Enlightenment, and Responsibility.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".