Bibliographic record
Abstract
In January 2019, the towns of Moose Jaw, Canada, and StorElvdal, Norway, engaged in a tongue-in-cheek spat over the size of their moose (Alces alces) statues. At 9.80 m in height, the Canadian town's “Mac the Moose” had long been the world's tallest. In 2015, however, Stor-Elvdal erected “Storelgen” (literally, The Big Moose). Storelgen was 30 cm taller, putting Moose Jaw's nose out of joint. Mac was a brown, cartoonish, wire-and-concrete affair, while Storelgen was sheer liquid beauty, fashioned from steel with the glimmering appearance of quicksilver (Figure 1). But that wasn't what bothered the Canadians. The Norwegian moose was bigger! After trading mock blows, the North Americans eventually conceded defeat to their new Scandinavian friends. But they knew not all was lost: Tallest Statue is not the only moose award to be had. ©Wafuefotodesign/Dreamstime.com What about Who's Got the Most Moose? Certainly, the Canadians this time hammer the Norwegians, at least in the absolute numbers game. Canada may have 500,000 to 1 million moose, while Norway can muster only 120,000 to 150,000. The US, with around 300,000 (including Alaska), can't compete; only Russia with 600,000 has a look-in. Total moose, however, is not the only possible basis for this award. If it's moose per square meter you're talking about, Sweden wins it hands down. With a massive 400,000 moose in just 447,000 km2, it's a runaway winner. Even granting the Canadians all of those 1 million moose doesn't cut it against a surface area of 9.98 million km2 (if you really want this in moose per square meter, do the math yourself!). Sweden's huge moose stash allows for an annual hunt of 80,000 to 100,000 animals, which in meat terms equates to nearly 10% of the country's beef production. Yet in the early 20th century, moose were quite rare in Sweden (although this didn't stop the October 31, 1928, issue of the Pinckney Dispatch, a local newspaper of Livingston County, MI, reporting them to be threatening the Swedish match industry by feeding too generously on the aspen trees from which matches are made). However, changes to hunting laws, cattle grazing practices in forests, and especially logging management (which provided clearings where moose can easily feed) collectively secured Sweden's top spot as most dense in moose. And then there's Biggest Moose. Even more room for trouble here! Which subspecies (there are seven)? By body weight or antler size? By individual or in general? The Alaskan moose, however, is generally regarded as the largest of all, and the biggest one ever recorded, a bull weighing over 1800 pounds, was hunted in that state. But watch out US, they live in Canada too, and Russia's Chukotka moose is also a whopper. Maybe one day… Among the minor awards available, Best Moose Cheese is clearly won by Sweden, the only country to make it (selling at hundreds of dollars per pound!). And Best Use of a Moose is a tie between St Albert, Canada (where a team of the cervids once pulled a mail buggy), and Sweden (where they once powered the sleighs of royal couriers). But there are also Ig Nobel-type awards. That for Most Embarrassing Moose-Care Incident goes to Danish astronomer Tycho Brahe's niece's husband. Born into old money, Brahe could afford to keep a moose, but around 1591 he kindly sent his animal – as a gift – from his estate in Scania (Sweden) to his nobleman friend and colleague Landgrave Wilhelm IV. It travelled by way of Landskrona Castle, where it was left in the charge of Brahe's relative, who managed to kill it within days. Apparently, the animal entered the castle and slipped into a room where it drank itself senseless on beer before tumbling down some stairs and breaking its leg. The poor thing died soon after. What, couldn't anyone shut a door? But the award for Action Most Indicting of Mankind in a Moose Context goes to the early settlers of Cape Breton Island, Nova Scotia. In his Historical and Statistical Account of Nova-Scotia (1829; Halifax, Canada: Joseph Howe), Thomas Haliburton denounced At the period of the establishment of the English in the Island, these animals became the object of most destructive pursuit, merely for the sake of their hides. Their carcasses were left by hundreds along the coast…and to such an extent [was] the butchery [that] as vessels passed by, the stench wafted from the shore was insufferable. Ever since the commission of that indiscriminate massacre, the numbers of the moose have been comparatively scanty. Fortunately there are now some 1300, the descendants of just 18 introduced individuals, though sadly this figure represents a decline from a high of around 5000. Finally, the award for Place You Never Expected to Find a Moose goes to China. Yes, there are moose in China! And Storelgen was actually cast there! Could that mean China might one day build its own, even taller moose statue? Maybe sleep is already being lost in Norway! Adrian Burton
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.482 | 0.176 |
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".