Knowledge and Data: An Exploration of the Use of Inuit Knowledge in Decision Support Systems in Marine Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In increasingly data-driven marine and coastal management practices, the issue of “data” is becoming central, resulting in the development of comprehensive data hubs and spatial data infrastructures. These data hubs are often composed of different types of datasets, from oceanographic to biological and socioeconomic. In the Canadian Arctic, and in the context of co-governance arrangements and participatory approaches, these data hubs include, prominently, Inuit knowledge. This chapter explores the ontological tensions of using Inuit knowledge as data in the context of marine and coastal management, and it discusses the nature of Inuit knowledge and the transformations that take place when the knowledge is rendered into data. The authors assess the ability of existing decision support systems and tools to incorporate Indigenous knowledge and propose a number of criteria to integrate Inuit ontological approaches in the design of these systems and tools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it