Bibliographic record
Abstract
In response to society’s expanding uses of technology, it is clear that the goals and contexts of schooling have, and are continuing to undergo a major redefinition. The continued and pervasive increase in the use of science and technology within our broader society has increased the perceived need to implement an increasingly technological perspective in schools and in curricula. This general trend towards incorporating more technology is evidenced by current STEM Initiatives seen worldwide. In this paper, using techniques such as narrative, analogy and metaphor, I will offer the beginnings of a socio-cultural and environmental critique to the current STEM movement. I will begin by examining ‘the roots’ of STEM and then follow this storyline with some of the more recent critiques and reforms aimed at broadening STEM perspectives (eg. STEAM and STREAM). I will then assert that students exposed to the STEM model of science education are being asked to understand environmental and technological issues only within prescribed or predetermined (political) limits. I argue that without the inclusion of an important socio-cultural critique, education of this nature works only to maintain and promote hegemonic beliefs and values while failing to address the collateral problems relating to our scientific and/or technological epistemologies. This paper goes on to describe an expanded and alternative framework that might define a more complex undertaking for education: one that involves a consideration of scientific, economic, ethical and aesthetic perspectives alongside each other. This modified ecological framework which I describe as ‘STEM and LEAF’ is then described with the intent of furthering an enhanced discussion and critique on the efficacy and suitability of the current STEM movement worldwide.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".