Open Networking in Central America: The Case of the Mesoamerican People's Forum
Bibliographic record
Abstract
This dissertation considers the case of the Mesoamerican People’s Forum (MPF), a Central American ‘cousin’ of the World Social Forum, and manifestation of the Global Justice Movement. It argues that the MPF cannot be adequately understood as a transnational social movement or as an ‘open space.’ Rather, it is best understood as a political playing field on which the leaders of locally rooted social movements contested the future of the Central American left within an uncertain and changing political context. Based on extensive ethnographic field work and grounded analysis, it argues that well-placed actors within forum spaces can best be thought of as ‘mediators’ between state and society. The emergence of de facto federated governance structures in Central America, plus weak democratic institutions, have placed new pressures on mediators. Leaders within the Central American left find that they need to build up and/or maintain power bases to shield their positions within an uncertain political environment. They mobilize people to participate in transnational forum spaces because of the legitimating benefits, but shape networked flows within these spaces to limit the potential for networking to erode established positions. Thus I conclude that openness is neither the condition nor the objective of social forums, but rather a pawn strategically deployed or retracted in the course of networked interactions. The work advances thinking about the nature of collective political subjectivity in an era of transformationalist globalization. It also argues in favor of critical realist perspectives on collectivization in a post-development, globalizing world. Specifically, scholars can best advance an ‘epistemology of the south’ by promoting and protecting cognitive justice, which in turn can be achieved through the use of realist approaches that serve to uncover the practices of power at work within networked spaces.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.014 |
| Scholarly communication | 0.012 | 0.007 |
| 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".