Conservation or Exploitation? Assessing the Education Impact of Accredited Zoological Institutions
Bibliographic record
Abstract
Zoological institutions, and the animals that inhabit them, have fascinated people since their inception. Over time, the mandates of zoos and aquariums have evolved and diversified beyond their sole anthropocentric focus on human entertainment. Today, zoological institutions have mandates to safeguard the populations of endangered species, protect wild spaces, and promote environmental and conservation education. This study seeks to answer the following questions: How are zoological institutions attempting to contribute to conservation through environmental education? Are they successful? Zoos and aquariums are in a unique position to play a role in fostering conservation and delivering experiential education opportunities to its visitors. Environmental education opportunities in zoological institutions raise awareness amongst the visiting public the ecological value of biodiversity, and the reintroduction of endangered species populations into the wild. Zoos achieve this through captive breeding programs and by collaborating on conservation programs with multiple stakeholders, including those who participate in citizen science projects. This thesis explores the effectiveness of the educational programs of zoological institutions and in communicating a conservation message. In addition, the concept of learning through experiential and deep learning is investigated to evaluate the potential for positive behavioural changes towards environmental stewardship. This study takes a qualitative multiple case study approach of three accredited zoological institutions – the Calgary Zoo, the Toronto Zoo, and the Vancouver Aquarium – to determine the effectiveness of their current conservation education messages. A social media analysis of the zoos’ Facebook pages and semi-structured interviews have been conducted with zoo volunteers to see if there is evidence of learning that might lead to stewardship and conservation behaviours in the zoos visitors. Additional insights into the impact that these educational efforts might have on conservation are provided through expert interview, personal observation, secondary literature, and grey literature. Findings suggest that experiential education programs are generating some conservation behaviours by members of the visiting public, particularly those who ultimately became volunteers at the zoos. The research also indicates that zoos could quite easily make more effective use of those volunteers and social media to more meaningfully communicate their environmental education programs, thereby enhancing and reinforcing the impact of their conservation work.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".