Science, Information and Policy Interface for Effective Coastal and Ocean Management
Bibliographic record
Abstract
Any book entitled "Science, Information, and Policy Interface for Effective Coastal and Ocean Management" is guaranteed to attract the attention of a wide, and curious, audience.Integrated Coastal and Oceans Management (ICOM) is a highly topical international issue.All governments (international, federal, provincial, municipal), economic sectors, and communities, are constantly pressurized by a multitude of interacting issues concerning policy, legislation, and operations on the use of resources in coastal and ocean areas.Accordingly, it is important for all of these entities to organize themselves (both individually and collectively) to produce, receive and act on information of common interest.In Atlantic Canada we have seen many provincial, federal, academic, and community programs and plans aimed at contributing to the process of integrating and coordinating policy on coastal and marine issues.Some examples include: Coastal 2000 (Nova Scotia Land Use Committee, 1994), Gulf of Maine Council on the Marine Environment, Eastern Scotian Shelf Integrated Management Plan (DFO 2007; McCuaig and Herbert 2013), Atlantic Coastal Zone Information Steering Committee (ACZISC), and the Bay of Fundy Ecosystem Partnership).Science and information flow for decision-making has formed a prominent part in all of these programs.The oceans surrounding Nova Scotia (The Gulf of Maine, Northumberland Strait, Bay of Fundy, and the Scotian Shelf) rank amongst some of the best studied and monitored marine areas in the world.The region has many wellknown commercial, research, academic, educational, government and non-government organizations involved in the generation and use of information for management of ocean and coastal resources.Despite this, the ICOM process, with its much-anticipated outcomes (IOC 2006), does not seem to have made much progress in Canada (DFO 2012dfo-mpo.gc.ca/ae-ve/evaluations/11-12/IOM-eng.htm).This might be explained by the diverse information requirements, and the characteristics of the numerous ICOM policy interfaces that are presented in this book.
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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.099 | 0.021 |
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".