A Proposed Safari Park in a Subtropical Forest in Northeastern Bangladesh Will Be Detrimental to Native Biodiversity
Bibliographic record
Abstract
Biodiversity in tropical and subtropical forests are at high risk of decline due to rapid anthropogenic development. Planned activities that potentially benefit communities near forests are often undertaken at the expense of forest biodiversity. Recently, the Government of Bangladesh released plans to develop a safari park in Lathitila forest in northeastern Bangladesh. This mixed evergreen, stream-fed, trans-border forest harbors 26 globally threatened species. The proposed plan aims to bring several exotic game animals such as the lion (Panthera leo), spotted hyaena (Crocuta crocuta) and cheetah (Acionyx jubatus) to be maintained in captivity. Additionally, exotic bird aviaries, gardens, a dolphinarium, a marine aquarium exhibit, and a carp pond have been proposed for construction. Here, we (i) summarize some of the key attributes of safari parks and the misconceptions associated with them; (ii) highlight some of the planned development activities of the proposed safari park; (ii) list the threatened species found in the area, and (iii) explain why establishing a park in the area would be detrimental the region’s biodiversity. We urge the government to abandon the plans to develop a safari park and suggest that the area be brought under formal protection for the benefit of biodiversity conservation.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".