Cautionary considerations for positive dingo management: a response to the Johnson and Ritchie critique of Fleming et al. (2012)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Johnson and Ritchie (2012) have provided a criticism of our opinion piece (Fleming et al. 2012). There is some common ground, but we remain unconvinced by their view that our reasoning was unsound or beside the point. In this response, we discuss where Johnson and Ritchie have provided unconvincing evidence to refute our seven considerations, and reiterate and demonstrate why these considerations remain important. The mesopredator release or suppression hypothesis in Australian ecosystems must be objectively evaluated before positive management of dingoes and other free-ranging dogs is recommended or implemented. Adaptive comanagement of free-ranging dogs can be used for both biodiversity conservation and the mitigation of livestock predation but caution must be exercised when considering using free-ranging dogs as a conservation tool.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it