Bibliographic record
Abstract
This is the second in what I plan to be a series of books featuring selected groups of Alberta insects.The first book of the Alberta Insects Series was about tiger beetles, and the volumes that follow will, if all goes well, treat ladybugs, the larger moths (what I call the "big snazzy moths"), the dragonflies proper, and possibly the grasshoppers as well.Tiger Beetles of Alberta: Killers on the Clay, Stalkers on the Sand was an experiment of sorts, and in most respects I think it succeeded.One tiger beetle specialist called it "a splendid mix of science and élan."Another entomologist wrote to me to say " WOW, is the tiger beetle book ever great!I have been standing in the hall like an idiot exclaiming to everyone who goes by about it."That made me feel good.I think that most entomologists would love to write about their favourite bugs in a conversational fashion, if only the world of scientific publishing would let them.I'm very fortunate to be able to write in a less constrained style in these books.By contrast, in the "primary literature" of journal papers and technical works, all emotive language must be purged from the text.The result, predictably, is dull writing in which all authors sound pretty much alike.After more than two centuries of this sort of thing, scientific writing has become almost inaccessible to average readers, regardless of their intelligence or overall education.This saddens me, and I think it also weakens science by making its details seem less and less relevant to the rest of the thinking world.Scientists, however, behave one way in print and another way in person, and in so doing they make it clear that they are no more Vulcan-like than anyone else.(I assume that most people reading this will be familiar with the Vulcans of Star Trek fame, and their so-called logical outlook on life.)In person, scientists are people like any others.They discuss scientific matters with little or none of the stylistic constraints that they show on the printed page.This leads many people to think that the conventions of scientific writing are largely trappings.The trappings of dull-style science give the ritual of science (if I may be so bold as to call it such) an aura of objectivity, and that is what counts on a purely subjective level-the aura.It is my view that true objectivity (and objectivity is the usual justification for dry prose in science) is a matter of thinking clearly and self-honestly about evidence, and about the reasoning process that you use to link evidence to your conclusions.What the rest of your mind does at the same time is of no scientific consequence.The important thing, aside from correct logic and careful meas-
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.716 | 0.573 |
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".