Bibliographic record
Abstract
Whether or not people in advantages contexts around the globe recognize it, it seems clear that our world is in serious peril. While small fractions of populations enjoy safety, basic comforts and many luxuries, increasingly more people are suffering from job insecurities, a range of health problems and manipulation facilitated by mass surveillance systems. Meanwhile, as few benefit, most of us are threatened by devastating climate change, environmental spoilage and species losses — all apparently undermined by systematic democratic assaults. Although network conceptions of phenomena may suggest distribution of responsibilities for such ills, much data and argument place considerable blame on few rich pro-capitalist individuals (e.g., financiers) and groups (e.g., corporations, think tanks and transnational trade organizations). Given collusion of governments in such social and ecological injustices, it appears extremely necessary that power in masses of people be rallied to critically interrogate actions of powerful entities and develop and take social actions that may lead to increases in social justice and environmental wellbeing. An important context, in light of roles of fields of science and technology in enactment of power, for promotion of such critical and action-oriented civic engagement is school science. Such roles have, indeed, been acknowledged — at least in part — for about the last half-century through ‘science-in-context’ educational domains like ‘STSE’ (Science, Technology, Society, Environment) education. Such more contextualized approaches have, however, been marginalized in most contexts. They are either given little attention or treated in somewhat ‘token’ ways (given severity of harms) by emphasizing individual — albeit reasoned — choices, which happen to be a priority of many capitalists. Marginalization of potential critical and action-oriented science education seems to have, meanwhile, dramatically increased with recent advent of ‘STEM’ (Science, Technology, Engineering and Mathematics) education initiatives — many of which prioritize teaching and learning of ‘products,’ such as laws, theories and innovations, of STEM fields and skills to develop them, at expense of educating students about problematic STSE relationships and preparation for possibly-rectifying actions. Given its hegemonic influences, as discussed here, one approach to promoting ecojustice through science education may be through encouraging and enabling youth to develop commodities that are both functional and aim to maximize wellbeing for individuals, societies and environments (WISE). Studies of one teacher’s efforts in this regard suggest considerable successes with such WISE engineering — although, as reported here, successes seem to come at expense of some educational losses that have been tied to pro-capitalist science education. Although such tempered achievements may seem frustrating, those promoting social justice and environmental wellbeing through school science may be motivated by emergent successes and possibilities for mobilizing them across networks of living, nonliving and symbolic entities.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".