Interpretive by Design: Engaging a Community to Create Interpretive Park Signage
Bibliographic record
Abstract
Executive Summary This paper describes our experience of engaging community residents and stakeholders in a nine month process of designing interpretive messaging in a popular public park on Salt Spring Island, B.C. Located close to the downtown core, the park covers 56.6 acres with a trail length over 8 km, and serves multiple users including tourists. The need for interpretive signage was identified to facilitate park staff to manage park issues among multiple users, educate visitors on the importance of the park's fragile ecosystem, offer correct historical and cultural information, as well as manage behaviours of visitors within the park (e.g., litter, vandalism, protecting flora/fauna etc.). The process included two phases: to begin, we engaged in three months of initial consultations through 11 focus groups with 89 residents and 16 park and recreation professionals to explore their experiences with and knowledge of the park. From the analysis of the focus group data, the general content of six signs were identified as important for the park: history, ecology, park behaviour guidelines, dog walking guidelines, directional sign, and one about the health benefits of being in nature. As well, a connecting theme emerged that captured the core beliefs, values and attitudes of focus group participants with regards to the park that we labeled “by nature.†This was followed by three months of designing and piloting 6 draft signs with 104 residents and 56 tourists who completed brief surveys about language, visuals, and comprehension. In the second phase, informed by the piloting results, signs were finalized, constructed and mounted in the park, and 68 park visitors were surveyed to evaluate the influence of the signs on their learning and park experience. We also gathered observational data using the Physical Activity Resource Assessment to assess the impact of the signs on park incivilities. In sum, a total of 265 Salt Spring residents and tourists contributed to the content and design of 6 signs in Phase I of the project. In Phase II, evaluation data from 63 park visitors revealed the signs to be very well received as evidenced by high scores for comprehension, interest and improved park visits. Answers to open ended questions on the survey confirmed the numerical ratings: 95.6% reflected positive terms, with ‘informative,' and ‘interesting' the most oft included terms. One year following their placement, none of the signs have been vandalised or stolen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".