The opaque 21<sup>st</sup> C reversed polarity default paradigm: ON
Bibliographic record
Abstract
Keeping pace with the ever-changing global landscape in terms of energy usage, carbon footprint and resource extraction is critical for environmental education (EE). For most of modern human history, the standard behavior for every day, household or institutional use of electricity in appliances, vehicles and lighting has been ‘off until turned on’. 21<sup>st</sup> century use of electricity in information and communications technologies including AI, ‘smart’ appliances, computers or buildings has reversed this polarity. It is argued in this paper that the new polarity is “ON” and that this opaque phenomenon may be creating a mindset involving “inattentive blindness” and “culpable ignorance” in regard to digital pollution. Rather than promoting an ecologically conscious mindset that critically examines personal and community involvement, this new, anesthetized mindset is flowing in an uncritical direction. EE curriculum needs to provide a critical focus on digital pollution and digital sobriety.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".