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Record W4407137069 · doi:10.1080/09500693.2025.2460048

Science education for growing networks of critique and altruism: striving for increased social justice and environmental vitality

2025· article· en· W4407137069 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Science Education · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsVitalityAltruism (biology)Economic JusticeSocial justiceEnvironmental justiceEnvironmental educationSociologyEnvironmental ethicsPsychologySocial scienceSocial psychologyPedagogyPolitical scienceLaw

Abstract

fetched live from OpenAlex

In the 1998 policy document, Beyond 2000, authors suggested that school science tends to prioritise education of few potential scientists. Apparently, little has changed since then. Given multiple apparent crises, however, like the climate emergency, it seems imperative that school science (or ‘STEM’) education be dramatically transformed to prioritise social justice and environmental vitality (‘ecojustice’). This, however, seems challenging. School systems appear enmeshed in tightly-woven networks of living, nonliving and symbolic actants apparently generally collaborating to maximise elites’ profits while compromising wellbeing of most other (a)biotic things. After elaborations of claims like those above, however, a science/STEM education framework that aims to help develop cultures of ‘critical altruism’ promoting increases in ‘ecojustice’ is described and critically defended. Some elements of this programme may be useful – albeit with caveats – to curriculum developers with similar goals. It prioritises direct instruction about apparently problematic relationships among fields of STEM and societies and environments and preparation of students for implementing their well-researched actions to help overcome issues in such relationships concerning them. Although this pedagogy seems to have had successes, it also appears that much work is needed to help spread values inherent to it across larger, perhaps more global, material-semiotic networks.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.717
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.329
Teacher spread0.323 · 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