Welcome to 310 Environmental Working Group! A Group Project That Places Students in the Role of Consultants Helping Businesses Choose the Most Climate Friendly Fluorinated Gas
Bibliographic record
Abstract
The Montreal Protocol is an international treaty that controls substances that deplete the ozone layer. Through the control of halogenated gases, it has been one of the most successful climate legislations to date. This success is driven by the interplay between chemical regulation and smart chemical design, demonstrating the positive impact chemistry can have on the world. This Article describes a group project that includes four assignments, a group presentation, and a writing task where students take on the role of consultants to assess the environmental friendliness of two fluorinated gases. Through the assignments students determine the global warming potential of two chemicals and pair this assessment with an evaluation of their potential to produce persistent products, such as trifluoroacetic acid, via atmospheric oxidation. Students worked together to take these, sometimes conflicting, pieces of evidence to make a final recommendation to their client as to the most "environmentally friendly" option in a mock Board of Directors meeting and then individually through a written recommendation. The project effectively addressed the learning goals of a third-year environmental chemistry class and was well received by students as a means of contextualizing the course material and providing students with a clear peer network in the class. This project is an effective application of fundamental chemistry topics (e.g., spectroscopy and the relationship between structure and reactivity) within a real-world context that emphasizes the ability of chemistry to have a positive impact on important environmental issues such as climate.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.451 | 0.249 |
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".