Mobilizing Consumers to Take Responsibility for Global Social Justice
Bibliographic record
Abstract
This article studies the antisweatshop movement's involvement in global social justice responsibility-taking. The movement's growth (more than one hundred diverse groups) makes it a powerful force of social change in the new millennium. The rise of global corporate capitalism has taken a toll on political responsibility. As a response, four important movement actors—unions, antisweatshop associations, international humanitarian organizations, and Internet spin doctors—have focused on garment-production issues and mobilized consumers into vigilant action. The authors examine these actors, their social justice responsibility claims, and their views on the role of consumers in social justice responsibility-taking. The authors determine four paths of consumer action: (1) support group for other causes, (2) critical mass of shoppers, (3) agent of corporate change, and (4) ontological force for societal change. The authors find that the movement mobilizes consumers through actor-oriented and event-specific (episodic) framing and offer a few results on its ability to change consumer patterns and effect corporate change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".