Bibliographic record
Abstract
Introduction Some 15 years ago, when I began studying waste issues, I was facing a long commute to and from work that involved waiting for a series of buses and the metro. As is often the case with commuters, we sometimes struck up conversations while waiting for our public transportation. After a number of these conversations, I noticed a trend: when asked about my work, and telling people that I research waste issues, I always got the same response. One hundred per cent of the time. The responses would go something like this: “I feel so bad about all of the garbage we have everywhere. I try to recycle as much as I can.” Sometimes my temporary travelling companion would go on to say that she, he or they did not know which recycling bin to put a certain item in. Sometimes the person would add that they had a neighbour/friend/family member that did not recycle as well as they should. Mainly women detailed teaching their children how to recycle. Now, years later, I am honoured to be regularly asked to give public presentations to community groups about waste issues. And my talks are uniformly met with the same range of questions that centre on one theme: how do we recycle more and better? As Chapter 2 details, local and national governments, manufacturing and retail industries, and many non-governmental organizations concentrate on recycling. For instance, numerous local grass-roots ‘zero waste’ organizations across North America, Europe and the Antipodes are working towards achieving zero-waste lifestyles, which often, if not mainly, involves increasing their members’ recycling behaviours. This focus is based on a number of assumptions that I will challenge in this chapter. The first premise is that increasing recycling decreases waste. Simply put, the assumption is that if we divert objects from the trash can and into the recycling bin, then we are decreasing our overall waste production. The second, related, premise is that by recycling, we are significantly decreasing our waste’s global environmental footprint. Put another way, the assumption here is that individuals and families produce our waste problem, and individuals and families can (and must) resolve this problem through increased and better recycling behaviours.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.038 | 0.004 |
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".