PROFILE The Perceived Implications of an Outsourcing Model on Governance within British Columbia Provincial Parks in Canada: A Quantitative Study
Bibliographic record
Abstract
Abstract Good governance is of paramount importance to the success of parks and protected areas. This research utilized a questionnaire for 10 principles of governance to evaluate the outsourcing model used by British Columbia Provincial Parks, where profit-making corporations provide all front country visitor services. A total of 246 respondents representing five stakeholder groups evaluated the model according to each principle, using an online survey. Prin-cipal component analysis resulted in two of the 10 princi-ples (equity and effectiveness) each being split into two categories, leading to 12 governance principles. Five of the 12 criteria received scores towards good governance: effectiveness outcome; equity general; strategic vision; responsiveness; and effectiveness process. One criterion, public participation, was on the neutral point. Six criteria received scores below neutral, more towards weak gover-nance: transparency; rule of law; accountability; efficiency; consensus orientation; and, equity finance. The five stake-holder groups differed significantly on 10 of the 12 prin-ciples (P \\.05). The 2 exceptions were for efficiency and effectiveness process. Seven of the 12 criteria followed a pattern wherein government employees and contractors reported positive scores, visitors and representatives of NGOs reported more negative scores, and nearby residents reported mid-range scores. Three criteria had government employees and contractors reporting the most positive scores, residents and visitors the most negative scores, and NGO respondents reporting mid-range scores. This research found evidence that perceptions of governance related to this outsourcing model differed significantly amongst various constituent groups.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".