Arts-based analysis of conservation education field trips for young people to observe wild lemurs in Southern Madagascar
Bibliographic record
Abstract
Opportunities for young people to directly experience nature can have positive impacts on the individual, the social group and on society as a whole, through future increased conservation action. We developed a program which engaged young people from Fort Dauphin in a field trip to see wild animals at Nahampoana Reserve. Our aim in offering field trips to young people living in the city was to create a positive emotional opportunity to engage directly with nature with the ultimate goal of protecting lemurs and their habitat. In our analysis, we predicted that participants who completed a survey after a presentation and field trip (assessment post field trip) would recall more correct and detailed facts than those participants who completed their surveys after the presentation only (assessment pre field trip). Our program used a variety of arts-based data collection methods including an initial essay writing component on conservation of lemurs and drawing analysis of observed plants and animals. Our results show, in part, that (A) initial written essays by participants showed misperceptions about lemurs, (B) participants who had attended the field trip prior to drawing their favourite aspect of the reserve, produced more species-specific plant depictions, and (C) participants who were involved in a presentation, field trip, and final group discussion came up with four principles for protecting lemurs and their environment. Upon analysis after the study, we gained the additional insight of being able to evaluate our survey methods.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".