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Record W2156209816 · doi:10.1509/jmr.12.0067

Seeing the Big Picture: The Effect of Height on the Level of Construal

2014· article· en· W2156209816 on OpenAlexaff
Pankaj Aggarwal, Min Zhao

Bibliographic record

VenueJournal of Marketing Research · 2014
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConstrual level theoryPerceptionPsychologyCognitionAffect (linguistics)Social psychologyCognitive psychologyMental representationCommunication

Abstract

fetched live from OpenAlex

Drawing on research on grounded cognition and metaphorical representation, the authors propose and confirm in five studies that physical height, or even the mere concept of height, can affect the perceptual and conceptual levels of mental construal. As such, consumers who perceive themselves to be physically “high” or elevated are more likely to adopt a global perceptual processing and higher level of conceptual construal, whereas those who perceive themselves to be physically “low” are more likely to adopt a local perceptual processing and lower level of conceptual construal. This difference in construal level also affects product choices that involve trade-offs between long-term benefits and short-term effort. The authors address alternative accounts such as vertical distance, visual distance, and perceived power. By highlighting the novel relationship between height and construal level, these findings contribute to research on grounded cognition and construal-level theory while also providing practical suggestions to marketing managers across a variety of domains.

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)0.005
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.304
GPT teacher head0.457
Teacher spread0.153 · 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 designObservational
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

Citations79
Published2014
Admission routes1
Has abstractyes

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