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Record W7132937633

As far as the eye can see: Visual metaphor in natural, man-made, and social contexts

2007· dissertation· W7132937633 on OpenAlexaff
Michelle C. Hilscher

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsCanadian HeritageLibrary and Archives Canada
Fundersnot available
KeywordsMetaphorExperiential learningLiteral (mathematical logic)Focus (optics)Product (mathematics)Literal and figurative languageSample (material)CognitionFunction (biology)
DOInot available

Abstract

fetched live from OpenAlex

This study investigated literal and metaphorical development of natural, industrial-architectural, and social themes. There were three parts to this study. Experiment 1 and 2 established a quantitative and qualitative framework for assessing participants' cognitive and affective responses to paired images differing in relationship and semantic context. Experiment 3 compared functional and experiential metaphors in design products with a Dutch sample of participants. Results suggested that metaphorical image pairs were intrinsically interesting and inspired learning goals whereas literal image pairs were approached with an extrinsic focus on performance. With regards to metaphors in design, it was revealed that experiential metaphors created an illusory atmosphere for product use, an appreciation of which relied on participants' simultaneous awareness of the tenor and vehicle. On the other hand, functional metaphors were characterized by a melding of form and function such that the vehicle residing within the concrete tenor realistically explained product use.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.394
Teacher spread0.379 · 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
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
Published2007
Admission routes1
Has abstractyes

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