A scoping review of Indigenous Cultural Mapping of coastal, island, and marine environments
Bibliographic record
Abstract
Indigenous Cultural Mapping (ICM) has the capacity to contribute to sustainably managing Sea Country. While there is a growing community of practice using ICM of marine, island, and coastal areas to incorporate Indigenous knowledge and cultural values into sustainability and conservation efforts, the literature is widely dispersed, and the method is not clearly defined or described. This scoping review evaluates the breadth and depth of practice undertaking ICM in island, coastal, and marine areas as captured within the English language scientific and grey literature. The objectives of this review were: 1) to determine the extent to which ICM is used a tool to manage Sea Country; 2) to evaluate the methods used throughout the process of ICM; and 3) to assess the studies against Arnstein’s (1969) ladder of participation. We used the Population Concept Context framework, searched Scopus, Web of Science, and Informit databases and Google Scholar, and identified studies that mapped Indigenous culture and/or cultural values in Sea Country. We included 54 studies that used ICM methods and were focused on Sea Country. These studies contribute to a growing body of work that demonstrates the value Indigenous knowledge adds to the sustainability of Sea Country now and into the future. High-level power-sharing and partnership throughout the research process is critically important. However, a lack of consistent standards of practice perpetuates research practices that exclude Indigenous communities from the research cycle. This limits the ability of ICM to improve sustainable practices that conserve and protect Sea Country. • Review articles were distributed around the globe, but most frequently situated in the United States, Australia, and Canada. • The published research incorporating Indigenous knowledges has increased over the past two decades. • Methods are poorly described, or defined, using a wide range of terms, with the majority described as participatory. • Variations in levels of participation are perpetuating practices of tokenism and excluding Indigenous communities. • Standards of practice and policies are needed to improve the interface between knowledge systems.
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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 | 0.024 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.034 | 0.035 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".