Bibliographic record
Abstract
Introduction When I was about nine years old, my mother patiently taught me how to knit. As we sat in her tiny sewing room and she showed me the impressive collection of yarn, knitting needles and patterns that she had collected throughout her life, my mother handed me a rigid spherical ball – two equal parts that could be screwed together, hollow on the inside and with a small circular hole in one of the halves. My mother explained that a plastics company had invented this ball ostensibly to keep the wool from either unravelling or being soiled. She said that after World War II companies were inventing anything and everything to make with plastics. Even as a child of the later 20th century, immersed from birth in a plastics world, I remember thinking that this was a strange object. Many years later, as a waste studies researcher, I find this object in equal measure both unsurprising and shocking. Plastics characterize our contemporary society. They proliferate within our homes and workspaces, are embedded in the fabric of our clothing, footwear, personal hygiene products, our bicycles, cars and other modes of transportation, our food, and even the human placental barrier. Like the proverbial lobsters in a slowly heated pot, we have become so accustomed to plastics’ incessant overabundance that we are overwhelmed by our current plastics waste crisis. From the giddy ‘miracle’ years of plastics and their seemingly limitless applications and everyday benefits to the public’s current disaffected dependence on plastics, this chapter focuses on how plastics have been framed by, primarily, the oil and gas industries that provide the raw materials needed to make plastics, and governments trying to appease publics’ growing concerns with plastics’ negative impacts on human health and the environment. Over 170 countries, from Canada to Kenya, the United Kingdom to China, Zimbabwe to India, have signed on to ‘significantly reduce plastics’ by the year 2030 (Masterson, 2020: np). At the same time, oil and gas industries have steadily (and sometimes exponentially) increased their plastics production, and make no secret of their plans to increase plastics production further.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.057 | 0.006 |
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".