How Environmentally-Friendly is Whaling: An Ecological Perspective
Bibliographic record
Abstract
"Much of international debate about management objectives and appropriate utilization of both whale and elephant populations centres on whether it is appropriate to regard these stocks as being essentially the same or fundamentally different from other biotic or mammalian resource stocks. Increasingly it appears that sectors of western society imbue both whales and elephants (and certain other selected species, e.g. see Kellert 1986) with a special status that requires that they be treated fundamentally differently from other species for management and conservation purposes. \n \n"The special status accorded whales and elephants comes in part from their biological characteristics, though very often these may be imputed or imagined biological characteristics rather than scientifically established ones. For example, the question of 'intelligence,' or communication abilities, or behavioral or social characteristics of these particular animals are areas where sentimentality, imagination, extreme anthropomorphization, or mere wishful thinking frequently overtakes the available scientific evidence. Unfortunately it is not only non-scientists who suffer lapses of critical thinking in regard to these matters (though often these scientists are non-specialists in the areas of science they uncritically embrace). \n \n"It is easy to be misled in these matters, as government officials, public figures, the media and various national and international organizations promote the impression that whales and elephants are highly intelligent, seriously endangered and subject to needless and irresponsible slaughter and consequently in urgent need of total protection. \n \n"Many scientists associate themselves with these 'environmental' campaigns. Championing a popular 'green' cause certainly can provide a welcome change from labouring in relative obscurity, as public advocacy may result in invitations to speak and be consulted, the promise of travel, and, perhaps, enhanced access to research funds."
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".