Bibliographic record
Abstract
TABLES 2.1 Timeline of selected policies and court decisions related to ocean reconciliation 18 2.2 Proposed criteria for reconciliation based on UNDRIP 22 2.3 Reconciliation of ocean issues in Canada 23 3.1 Notable rapid changes events in Canada 47 4.1 Past trends and future projections of mean total higher trophic level biomass 70 for the Canadian exclusive economic zones and the North Atlantic Ocean 5.1 Proposed matrix framework for representing a set of plausible scenarios 80 5.2 Summary of the five Shared Socio-Economic Pathways 80 5.3 Summary of scenario archetypes and their application to development of 81 OceanCanada Partnership scenarios 5.4 Assumed values for socio-economic variables used to calculate indicators 82 5.5 Summary of scenario narratives for three potential pathways and their 84 implications for Canadian fisheries and marine ecosystems 5.6 Projected percentage change in species abundance and fish catch potential 85 in 2050 relative to 2015 5.7 Estimated employment, fish supply, and change in landed value per fisher 85 in 2050 relative to status quo under each scenario 8.1 Access in 2019 to adjacent areas as defined by the allocation under direct 130 control of co-management boards or land claims agreements directly 9.1 Synthesis of lessons and policy recommendations 154 10.1 Governance factors that shape knowledge co-production 162 10.2 Contextual factors for knowledge co-production 169 11.1 Evaluations of seven case studies 180 13.1 Summary of 50 interviews conducted in the Magdalen Islands and abroad 217 13.2 Summary of the four case studies 218
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.
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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.811 | 0.592 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".