Bibliographic record
Abstract
Species of invertebrate animals, notably insects, are undergoing an alarmingly high rate of extinction, coupled with minimal support for their protection, even from the world’s leading conservation organisations. This is intolerable, as invertebrates constitute over 95% of the world’s species, have indispensable economic values and provide ecological services without which life on earth would virtually cease. Much of the lack of public and governmental support for invertebrate conservation is due to the abhorrent tiny pests that have persuaded most people that ‘bugs’ are bad and consequently the only species worthy of support are the charismatic superstar mammals like pandas and tigers that currently are the mainstays of biodiversity fundraising. Just as these respected, highly attractive icons are effective ambassadors of biodiversity conservation, so certain detested pests have poisoned the public image of invertebrates, and indeed have made it seem to many that most wildlife is hostile. The ‘dirty dozen’ bugs that particularly are a hindrance to improving public investment in biodiversity are: bedbugs, clothes moths, cockroaches, fleas, houseflies, leeches, lice, locusts, mosquitoes, spiders, termites and ticks. Except for spiders, these species, admittedly, are responsible for enormous damage to health and economic welfare. Nevertheless, this paper shows that most have at least some compensating values, their harm has often been exaggerated and all have related species that are good citizens. Six of the dozen ‘least wanted’ invertebrates highlighted are blood parasites of humans, and these ‘bad apples’ are very hard to defend since parasitism seems abhorrent. Remarkably, however, at least half of the world’s tens of millions of species are also parasites, and without them most ecosystems would be in danger of collapse. To improve invertebrate conservation, it is advisable that efforts be made to educate the public regarding their importance. Since prejudices against ‘bugs’ are primarily acquired during childhood, special attention is needed to persuade the young that most invertebrates are harmless, valuable and entertaining. Recent advances in genetic engineering (‘synthetic biology’, ‘genetic drives’) have led to very serious consideration of deliberately eliminating the world’s worst pests of humans. While these extermination technologies could greatly increase support for invertebrate conservation by annihilating their most despised representatives, the dangers of unforeseen damage to ecosystems and hence to biodiversity are substantial.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".