Worlds, words, and spaces of resistance: Democracy and social media in consumer co-ops
Bibliographic record
Abstract
This article explores how members of one of the largest Canadian consumer co-ops, reacting to what they saw as an assault on its democratic principles, use social media to try resisting the attempt from the board of directors to change its governance rules. Building on the Economies of Worth and Critical discourse analysis joint framework that considers power relations in the justification context, we unveil two essential moments. Initially, our analysis points to hegemonic justification struggles marked by the board and resisting consumer-members drawing on and reordering multiple worlds to debate the risk of democratic degeneration in consumer co-ops. Second, the critical insights suggest that the hegemonic control over the official deliberative arena pushed dissenting actors toward social media, an alternative space where they could deconstruct the co-ops-controlled discursive arena and create new conditions of possibility. Our article contributes to the literature on democratic degeneration in alternative organizations. More specifically, in the case of large consumer co-ops in which consumer-members have limited embodied presence, our results highlight how social media can offer a new space for debates, dissensus, and critical deconstruction. Our research also extends the post-structural criticism of the domination tendency of rational debate frameworks by showing that strategic displacement to new alternative spaces is essential to create new possibilities beyond those in central discursive arenas.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.021 | 0.103 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".