Promoting Inclusive Outdoor Recreation in National Park Governance: A Comparative Perspective from Canada and Spain
Bibliographic record
Abstract
While national parks (NPs) have for a long time made substantial contributions to visitor well-being, many spaces remain out of reach of people with disabilities (PwDs). This is partly due to a lack of policies that take accessibility for broader intersectional audiences into consideration. This paper evaluates governance and legal frameworks in NPs in both Canada and Spain. A decision-making framework based on intersectionality realities is proposed to assess current conditions of environmental good governance using a set of descriptors created to scrutinize laws and technical documents that can promote equitable access to NPs. To validate results derived from the regulatory evaluation, semistructured interviews with park managers were carried out. Results revealed the importance of incorporating equity discourses into policies that regulate NP networks to guarantee that all the intersectional realities for park uses are considered in their management. Furthermore, when a country develops a well-structured federal framework under which the rights of PwDs are ensured, it transcends other fields of law. Differences between the Canadian and the Spanish situation are highlighted, as well as the need for links between higher-level policies and laws and on-the-ground implementation, with NP management plans playing an important role.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".