Opportrirlities and Cltalleirges for Protectirrg, Rcstorirrg arid Errhafrcirrg Coasral I-iabitats ill the B(i,v ofFti11dy hlOVlNG TOWARDS A COASTAL BIOSPHERE RESERVE IN ATLANTIC CANADA SOME LESSONS FROM THE SCOTIAN COASTAL PLAIN'
Bibliographic record
Abstract
The UNESCO biosphere resenre concept has been proposed as an approach to the conse~vation and sustainable management of coastal areas in Atlantic Canada- specifically southwestern Nova Scotia and the Bay of Fundy. A preliminary assessment of tlie feasibility of developing l l~e concept in coastal southwestern Nova Scotia concluded that the area meets the international criteria for biosphere reserves; that there are inany underlying resource use and socio-cultural issues that may be challenges or opportunities in further development of the concept; and tliat i t is the role of the biosphere reserve as a niechanisni for enhancing local, regional, and nit~lti-j~lrisdictionaI cooperation that is most needed in tfie area. Issues raised during the study may be relevant to the development of tile biosphere reserve concept in the Bay of Fundy or elsewhere in the Atlantic region. This paper represents an attempt to draw out generic lessons learned tltat may scrve as feasibility criteria for tlie developnlent of coastal biosphere resenies
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".