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Record W2065470335 · doi:10.1075/ml.6.3.04zha

Topological spatial representation across and within languages

2011· article· en· W2065470335 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Mental Lexicon · 2011
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsConcordia University
FundersFonds de Recherche du Québec-Société et CultureHeilongjiang University
KeywordsMandarin ChineseRepresentation (politics)LinguisticsPoint (geometry)Topology (electrical circuits)Computer sciencePsychologyMathematicsCombinatoricsGeometry

Abstract

fetched live from OpenAlex

This paper examines the commonalities and variations between and within groups of English and Chinese (Mandarin) speakers in using terms to refer to the topological spatial concepts of containment (expressed by in and related terms in English) and support (expressed by on and related terms in English). In addition to crosslinguistic similarities, systematic differences in the use of linguistic expressions by Mandarin and English speakers for these topological spatial relationships were found, as well as systematic individual differences within each language group. Together, these findings point to potential underlying differences in how speakers of English and Mandarin conceptualize these two topological spatial categories.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.059
GPT teacher head0.371
Teacher spread0.312 · 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