Bibliographic record
Abstract
Much of the world is experiencing a crisis in which many ‘instructional packets’ (SARS-CoV-2 viruses) have commandeered ‘machinery’ of living beings to propagate themselves — regardless of surrounding harms their self-interested purposes may cause. Although they have, indeed, caused massive global disruption, crises linked to hegemonic actors are not uncommon. Capitalists, like viruses, conscript various living and nonliving entities to serve them and, in their persistent — and, generally, highly-successful — pursuit of profit, are said to be responsible for numerous social injustices and much environmental devastation, such as climate disruption and nuclear war (Ripple et al., 2020). Accordingly, like viral pandemics, many suggest that capitalism is a ‘pandemic’ and also must be eliminated — and, some would suggest, replaced with eco-socialist worlds. Capitalism seems, however, to be extremely resilient, often able to survive different crises and, sometimes, capable of emerging even stronger. In this vein, Naomi Klein (2007) suggests that capitalists and others have routinely exploited natural and anthropogenic disasters — using societal destabilization to further implement pro-capitalist policies, often at expense of well-being of many people (e.g., gig workers), societies (e.g., under surveillance) and environments (e.g., climate change). The CoViD-19 pandemic, however, may be a special kind of crisis — perhaps opening doors to more non-capitalist futures. Although enabling, for instance, more for-profit surveillance, it also may have disaggregated capitalist networks to the point of severe weakening and, in doing so, enlightened many people about pre-crisis neoliberal and populist infrastructures that may have contributed to this and other crises. Such conscientization may, in turn, have emboldened many to work for better futures. Given roles of science and technology (S&T) in capitalist empowerment, a natural place for such transformation may be science and technology education. In this paper, a framework for S&T education showing promise in this regard is described and defended. Nevertheless, those wishing societal transformation towards more eco-socialist futures need to engage multiple and diverse living, non-living and symbolic entities in ways that may generate networks supportive of such transformations.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.163 | 0.042 |
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".