Toronto Zoo’s Elephant Keepers Show Extraordinary Efforts in Supporting Their Herd
Bibliographic record
Abstract
Their HerdThe Toronto Zoo recently decided to relocate their elephants to another facility and eliminate elephants from their collection.This is not something unusual in the zoo industry.Zoos and aquariums make difficult decisions like this on a regular basis.What made the circumstances unusual were the reported involvement of animal activists and politicians in the decision-making process, and the lack of involvement, even exclusion, of the animal care staff at the Toronto Zoo.Even more extraordinary was the reaction of the elephant keepers at the Toronto Zoo.The keepers took their frustration to the streets in old-school style, with the twist of some new technology.Using professionalism the entire way, they created a most unusual movement that hasn't been seen before in the animal care industry.I recently took the opportunity to speak with CUPE Local 1600, the union that represents the elephant keepers at the Toronto Zoo.What follows is an interview that is meant to help explain the situation and highlight the extraordinary efforts of these very dedicated animal keepers.AKF: Please give our readers a quick introduction to the situation.2012."Toronto Zoo's Elephant Keepers Show Extraordinary Efforts in Supporting Their Herd."Animal keepers' forum 39(1), 12-16.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.007 |
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".