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Record W7060294024

Analogy Reframed

2016· article· en· W7060294024 on OpenAlexaff

Bibliographic record

VenuePhilPapers (PhilPapers Foundation) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEmbodied cognitionAffordanceSemioticsCognitionAnalogySet (abstract data type)Cognitive linguisticsReflexive pronoun
DOInot available

Abstract

fetched live from OpenAlex

The evolution of arm-leg relationships presents something of a problem for embodied cognitive science. The affordances of habitual bipedalism and upright posture make our two sets of appendages and their interrelationships distinctively human, but these relations are largely neglected in evolutionary accounts of embodied cognition. Using a mixture of methods from historical linguistics, Cognitive Linguistics and linguistic anthropology to analyze data from languages around the world, this paper identifies a robust, dynamic set of part-whole relations that emerge across the human waistline between upper and lower appendage sets cross-culturally. The general pattern—identified as “arm-leg syncretism”—provides a plausible primary source for the uniquely human penchant for creative analogy, or “double-scope conceptual blending”, said to underlie the human language faculty (Fauconnier and Turner 2002, 2008; Deely 2002; Anttila 2003; Bybee 2010). This account not only addresses a conspicuous gap in the literature but also enables us to better understand what it means to be human—including how we came to be unique among other species and how we are still vitally interrelated with other species. Deely (2010) blends both sides of this tension into a single phrase: “the semiotic animal”. The paper further develops this distinction by drawing attention to one of the roles upright posture played in the emergence of semiotic consciousness.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.847
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.008

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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