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Rethinking Neandertals

2023· article· en· W4384488770 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Anthropology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPaleoanthropologyNeanderthalInterpretation (philosophy)Focus (optics)EpistemologyHistoryArchaeologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

In this article, I first provide an overview of the Neandertals by recounting their initial discovery and subsequent interpretation by scientists and by discussing our current understanding of the temporal and geographic span of these hominins and their taxonomic affiliation. I then explore what progress we have made in our understanding of Neandertal lifeways and capabilities over the past decade in light of new technologies and changing perspectives. In the process, I consider whether these advances in knowledge qualify as so-called Black Swans, a term used in economics to describe events that are rare and unpredictable and have wide-ranging consequences, in this case for the field of paleoanthropology. Building on this discussion, I look at ongoing debates and focus on Neandertal extinction as a case study. By way of discussion and conclusion, I take a detailed look at why Neandertals continue to engender great interest, and indeed emotion, among scientists and the general public alike.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.396
Teacher spread0.351 · 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