The Story of My Face: How Environmental Stewards Perceive Stigmatization (Re)produced By Discourse
Bibliographic record
Abstract
The story of my face intertwines concepts of social semiotics and discourse analysis to explore how a simple type of printed media (flyer) can generate stigmatization of informal recyclers, known as binners in Western Canada. Every day, media exposes humans to signifiers (e.g., words, photographs, cartoons) that appear to be trivial but influence how we perceive their meaning. Amongst the signifiers frequently found in the media, the word “scavengers”, has been used to refer to autonomous recyclers. Specific discourse has the potential to promote and perpetuate discrimination against the individuals who deal with selective collection of recyclables and decrease the value of their work. Their work is valuable because it generates income for recyclers, recovers resources and improves overall environmental health. In this context, the present qualitative study draws on data collected with binners during research conducted in the city of Victoria, in British Columbia. First we analyze a dialogue between binners from a participatory video workshop, to explore their perceptions of the stigma they suffer. Second we use a flyer produced by the local government alerting against scavenging to illustrate how the content (i.e., structural organization [text and images] in which they are embedded work together to mediate stigmatization against recyclers. Third, we analyze videotaped data from a panel discussion with local government, the local community, and binners on inclusive waste management, to uncover different negative perceptions of binners. In our study we look at the official discourse that marginalizes informal recyclers and creates social injustices. We illustrate how the recyclers perceive stigma and suggest that marginalization could be overcome by reiterating the image of environmental stewards instead of scavengers.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.042 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".