An Analysis of Fossil-Fuel Dependence in the United States with Implications for Community Social Work
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.
Bibliographic record
Abstract
This article examines fossil-fuel dependence in the United States with emphasis on the areas of transportation and food. It is argued that fossil-fuel dependence will cause significant social and economic problems in the future and that ongoing usage is a major contributor to mounting environmental degradation. Ultimately, the authors argue that our fossil-fuel based economy is unsustainable and that efforts should be taken to reduce usage and dependence. A growing community movement aimed at revitalizing local economies and reducing fossil-fuel usage has recently emerged. Social work can bring critically important values and knowledge to these and similar efforts, especially in regard to community organizing and the participation of marginalized populations. Key Words: Fossil Fuels, Energy, Sustainability, Local Economy, Community Organizing, Social Work
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it