Public Awareness, Education, and Marine Mammals in Captivity
Bibliographic record
Abstract
Increasing popularity of marine parks as tourist attractions brought with it a number of concerns. Considerable attention has been paid to investigate issues, such as the ethics of keeping marine mammals in captivity, welfare of captive marine mammals, and the educational and conservational abilities of marine parks. Little research has been conducted to explore the public's awareness and opinions of these issues. Public awareness is an important tool to understand the quality of a marine park's products and services. This study was designed to investigate the public's awareness of welfare of captive marine mammals, educational and conservational purposes of marine parks, and to examine public awareness and opinions of Dunlap and Van Liere's New Environmental Paradigm. A total of 120 respondents from St. Catharines, Canada completed either a visitor or a nonvisitor questionnaire. Results indicated that most people were aware of the issues of welfare of captive marine mammals and educational opportunities offered by marine parks, but showed less awareness of the conservational issues. However, results also indicated that respondents were well aware of, and agree with, the concerns expressed in the New Environmental Paradigm.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".