Claiming market ownership: Territorial activism in stigmatized markets
Bibliographic record
Abstract
Brands that seek to serve stigmatized markets are frequently targeted with activism by stigmatizers who hold discrediting beliefs about the products, practices and/or people associated with such markets. Drawing on an inductive analysis of a large set of qualitative data in the halal food and beverage market, we identify three triggers that make activism by stigmatizers more likely to occur: stigma multiplicity, identity threat to stigmatizers, and ambiguity in targeting. Findings show that the nature of such activism is territorial as stigmatizers claim market ownership. We identify three forms of this territorial activism: patrolling the market boundaries, punishing the insurgents, and projecting identity threats beyond the market. Our study contributes to the market systems literature and to theories of identity threat, ownership, and territoriality. It further proposes a number of strategic options for companies that are being, or may expect to become, the targets of activist stigmatizers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".