Paper submitted to the 8th International Conference of the European Society for Ecological Economics
Bibliographic record
Abstract
In response to accelerating ecological deterioration, many universities have made commitments to ensure they graduate ecologically responsible citizens and to integrate sustainability across the curriculum. This study involves a content analysis of how Econ101 textbooks address environment-economy linkages. In North America, introductory economics courses (‘Econ101’) are standardized and rely heavily on textbooks. A small number of textbooks dominate this market. Orthodox Econ101 textbooks in current use in British Columbia, Canada were included in the study as well as three leading US textbooks. These were contrasted against a pair of micro/macro texts explicitly written to address sustainability. The orthodox textbooks are found to largely ignore or misrepresent ecosystem-economy linkages and to include content that is unhelpful in furthering student understanding of sustainability and in providing them with the tools to contribute to its achievement. Universities that have made a commitment to integrate sustainability across the curriculum should examine carefully the textbooks used in their introductory economic courses and consider adopting textbooks that have explicitly integrated sustainability-relevant content throughout the text.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.236 | 0.060 |
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".