Bibliographic record
Abstract
While the notion of 'Canadian identity' tends to oversimplify the country's cultural diversity, \nit is frequently claimed that national identity is both reflected in and promoted by Canada’s \nNational Parks. This owes largely to the fact that the beginning of the National Parks system \nin the late nineteenth century, coincided with the formation of Canada as a country, and \nthat National Parks have been established in every province since. Yet despite the mandate \nof Parks Canada to preserve these landscapes for future generations of Canadians, their \ninconsistent approach to both land stewardship and to genuine cultural inclusivity exposes \nthe need for a new form of park management. Focusing on the proposed National Park \nReserve on the Hog Island Sandhills in Prince Edward Island, this thesis project prioritizes \na cooperative management model between Parks Canada and the local Indigenous \ncommunities while contributing to the site’s cultural and environmental sustainability. \nMobilizing design to critically (re)brand the National Park's architecture, its wayfinding \nand its promotional materials, this thesis project promotes the official (but inconsistently \nrespected) mandate of Parks Canada for landscape conservation while also prioritizing \nCanada’s stated (but not yet realized) commitment to Truth and Reconciliation.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".