MétaCan
Menu
← Back to cohort
Record W2992544686 · doi:10.1017/9781787445925.007

Bears, Wildmen, Yeti and Sasquatch

2019· other· en· W2992544686 on OpenAlexaboutno aff
Jeff Meldrum

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Humans have long held an affinity with bears, and a fascination for their superficial, but remarkable, similarity to people. This allure has even taken the form of worship, or arctolatry . Some have argued that the romantic notions of ancient bear cults and Paleolithic shrines are more the result of taphonomic processes and the imaginations of early discoverers (Wunn 2001). Wunn (2001, 457) concludes, ‘Conceptions of cave bear worship during the early and middle Paleolithic period belong to the realm of legend.’ Not all might agree, but in any case, in the more recent past, bear worship is manifest among ethnic groups across northern Eurasia, stretching from the Basques of the Pyrenees to the Ainu of Hokkaido. Intertwined with these practices is the frequent folk belief that humans descended from bears. For example, the ancient royal lines of Denmark and Sweden are declared to result from a cross between a woman and a bear (Magnus 1555). Indigenous peoples of North America also held the notion that bears and humans can interbreed. For example, the Haida of the Pacific coast of Alaska and Canada hold a tradition of a woman taken as a wife by a bear. The daughter of this pairing eventually returned to live with the Haida, and according to the legend, this primal bear-human goddess is the ancestor of all those entitled to wear the prestigious bear clan crest (Smith 1909). Bears exhibit notable likenesses to humans in both anatomy and behaviour. Bears walk on plantigrade feet, they can stand upright, they nurse their young from paired pectoral mammae as do humans, they are omnivorous and intelligent, and they have colour vision. Medieval physicians recognized the similarity between bears and humans and, prior to knowledge of the great apes, considered the bear one of the animals most closely related to humans (Pastoureau 2011). Poet and environmental activist Gary Snyder (1990, 175) mused, ‘After you take a bear's coat off, it looks just like a human.’ In fact, as any hunter who has dressed a bear carcass can attest, the resemblance in musculoskeletal anatomy is so striking that some texts on forensic anthropology include specific references to bear skeletal anatomy in order to differentiate it from human remains.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.001

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.

Opus teacher head0.006
GPT teacher head0.195
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicWildlife Ecology and Conservation→French-language works237,207→