Marine zoning for the Marine Plan Partnership (MaPP) in British Columbia, Canada
Bibliographic record
Abstract
A zoning framework was developed for the Marine Plan Partnership for the North Pacific Coast (MaPP) in order to provide guidance for decisions regarding coastal and marine economic development, marine resource management, and marine protection or conservation across the MaPP region, the Northern Shelf Bioregion, British Columbia, Canada. The MaPP Zoning Framework was developed over an 18-month period at the beginning of the marine spatial planning (MSP) process with stakeholder consultation and incorporated lessons learned from other planning efforts in British Columbia and globally. The three main requirements for the Framework included that it was applicable and flexible for use across the MaPP regional boundary, which included four sub-regions that had diverse priorities and marine activities, that guiding principles for zoning would provide consistency for policy and other decisions within the MaPP regions, and that zone categories synergized with existing policy and legislation. A stakeholder advisory process was used to develop the Framework which resulted in three zone categories to achieve the goals of MaPP: Protection Management Zone (PMZ), Special Management Zone (SMZ), and General Management Zone (GMZ). Zone identification included numerous factors such as species and habitat diversity, cultural values, existing uses and activities, and priorities for sustainable economic development and conservation. The Framework was effectively used to zone 102,000 km2 of the MaPP region during the MSP process for more than 15 different sectors that were within the scope of the MaPP partners’ jurisdiction. Importantly, the Framework was successfully adapted across the four distinct MaPP sub-regions and consistently applied for an effective regional approach to decision making and management for both First Nations and provincial governments.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".