The adaptation of a risk-based approach for integrated coastal management
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.In Canada, the development of risk-based approaches to support decision-making continues to be a priority for integrated coastal-zone management. The development of a conceptual framework for risk-based integrated management is considered as a means to more effectively use existing information and ensure the efficient deployment of resources as well as renewing the focus on priority setting. Strengthening the initial phases of this process is key to building a credible and pragmatic management process that has the potential to be successful at achieving realistic goals within a well-defined scope and scale of issues. The retooling of the best available information is being considered with regard to the development of environmental vulnerability profiles in order to incorporate: (i) ecologically significant areas, (ii) social-cultural and economically significant areas, (iii) human use activities and their zone of influence, and (iv) characterizing the potential conflicts and compatibilities. The intent is to provide the context to frame preliminary decisions with regard to the appropriate approach and level of response required to lead to more focused assessments relating to ecology, sociocultural and economic, and governance issues. The elements being considered are founded on the recognition of jurisdictional authorities and their respective accountabilities for the management of issues that cannot be resolved unilaterally by any organization or entity alone. Moreover, a risk-based framework is being examined as a means to provide an objective, rigorous, and iterative approach that may serve to validate facts and perceptions around public concerns while enhancing communication and engagement.
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 | 0.025 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".