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Record W1780044694 · doi:10.1098/rstb.2014.0356

Insights into early lithic technologies from ethnography

2015· review· en· W1780044694 on OpenAlexaff
Brian Hayden

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2015
Typereview
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLithic technologyDiggingOlduvai GorgePaleoanthropologyGeologyArchaeologyPaleontologyGeography

Abstract

fetched live from OpenAlex

Oldowan lithic assemblages are often portrayed as a product of the need to obtain sharp flakes for cutting into animal carcases. However, ethnographic and experimental research indicates that the optimal way to produce flakes for such butchering purposes is via bipolar reduction of small cryptocrystalline pebbles rather than from larger crystalline cores resembling choppers. Ethnographic observations of stone tool-using hunter-gatherers in environments comparable with early hominins indicate that most stone tools (particularly chopper forms and flake tools) were used for making simple shaft tools including spears, digging sticks and throwing sticks. These tools bear strong resemblances to Oldowan stone tools. Bipolar reduction for butchering probably preceded chopper-like core reduction and provides a key link between primate nut-cracking technologies and the emergence of more sophisticated lithic technologies leading to the Oldowan.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.007
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.140
GPT teacher head0.361
Teacher spread0.221 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations38
Published2015
Admission routes1
Has abstractyes

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