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Abstract Social‐ecological systems like fisheries provide food, livelihoods and recreation. However, lack of data and its integration into governance hinders their conservation and management. Stakeholders possess site‐specific knowledge crucial for confronting these challenges. There is increasing recognition that Indigenous and local knowledge (ILK) is valuable, but structural differences between ILK and quantitative archetypes have stalled the assimilation of ILK into fisheries management, despite acknowledged bias and uncertainty in scientific methods. Conducting a systematic review of fisheries‐associated ILK research (n = 397 articles), we examined how ILK is accessed, applied, distributed across space and species, and has evolved. We show that ILK has generated qualitative, semi‐quantitative and quantitative information for diverse taxa across 98 countries. Fisheries‐associated ILK research mostly targets small‐scale and artisanal fishers (70% of studies) and typically uses semi‐structured interviews (60%). We revealed large variability in sample size (n = 4–7638), predicted by the approach employed and the data generated (i.e. qualitative studies target smaller groups). Using thematic categorisation, we show that scientists are still exploring techniques, or ‘validating’ ILK through comparisons with quantitative scientific data (20%), and recording qualitative information of what fishers understand (40%). A few researchers are applying quantitative social science methods to derive trends in abundance, catch and effort. Such approaches facilitate recognition of local insight in fisheries management but fall short of accepting ILK as a valid complementary way of knowing about fisheries systems. This synthesis reveals that development and increased opportunities are needed to bridge ILK and quantitative scientific data.
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Against method: Exploding the boundary between qualitative and quantitative studies of science
Quantitative and qualitative studies of science have historically played radically different roles with opposing epistemological commitments. Using large-scale text analysis, we see that qualitative studies generate and value new theory, especially regarding the complex social and political contexts of scientific action, while quantitative approaches confirm existing theory and evaluate the performance of scientific institutions. Large-scale digital data and emerging computational methods could allow us to refigure these positions, turning qualitative artifacts into quantitative patterns into qualitative insights across many scales, heralding a new era of theory development, engagement, and relevance for scientists, policy-makers, and society.
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- Award ID(s):
- 1800956
- PAR ID:
- 10298865
- Date Published:
- Journal Name:
- Quantitative Science Studies
- Volume:
- 1
- Issue:
- 3
- ISSN:
- 2641-3337
- Page Range / eLocation ID:
- 930 to 944
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1162/qss_a_00056
