Bibliographic record
Abstract
The “big ” story of human progress has polarizing tendencies featuring the binary options of progress or decline. I consider human progress narratives in the context of everyday life. Analysis of the “little ” stories from two narrative environments focusing on peak oil offers a more complex picture of the meaning and contours of the narrative. I consider the impact of differential blog site commitments to peak oil perspectives and identify five narrative types culled from two narrative dimensions. I argue that the lived experience complicates human progress narratives, which is no longer an either/or proposition This is going to be an environmental disaster of unprecedented proportions and the only thing that people seem to really care about is keeping the Mississippi open to shipping traffic so that BAU [business as usual] can continue. I weep for the wetlands and what their loss will mean. “FMagyar ” April 30, 2010 What's the worst the doomers can moan about now? An oil spill (not even a big one by historical standards) and a bit of toxic mess in Canada. Woo, I'm so scared! Come on doomers, you can do better
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.032 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".