Perceptions of governance and access in artisanal marine fisheries in northern Brazil
Bibliographic record
Abstract
Artisanal fisheries form the basis of the livelihoods of millions of people in the Brazilian Amazon. Few empirical studies have characterized, however, how the governance of marine small-scale artisanal fisheries (SSF) in the Amazon, under the decentralized governance system in place, is perceived by those most affected. Drawing on Ribot and Peluso’s (2003) Theory of Access eight net-map interviews were conducted with key informants (small-scale and large-scale artisanal fishers, representative of civil society organization and public authority) to investigate how the local fisheries governance system is perceived to affect SSF access to fish and fisheries in Bragança (E of Pará, northern Brazil) between November 2022 and March 2023. Interactions are predominantly seen to occur between SSF as part of daily access negotiation processes. These processes take shape through interactions relating to knowledge of the biogeophysical environment and fishing, and conflict situations when customary fishing rules are not respected. Public authorities were seen to primarily control fishers’ legal access through inspections. Civil society organizations were perceived to be ineffective in facilitating access to benefits from public policies. Public authorities and civil society organizations were seen to leave a governance gap in terms of access for fishers. Vessel owners and post-harvest actors were seen by fishers as key regulators of SSF access to capital and markets. They control credits, set ex-vessel prices, and provide material resourcing that sustain power asymmetry. This study highlights key stakeholders’ perceptions of the range of relationships through which access to fish and fisheries is negotiated and contested. Our findings suggest that coastal fisheries governance in the Brazilian Amazon needs to address a number of factors influencing SSF, and more broadly, artisanal fishers’ access. This should occur alongside resolving immediate conflicts, with a consistent focus on equity and justice as systemic preconditions for sustainable human-nature relations in fisheries.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".