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Record W2739916508 · doi:10.5539/ijms.v9n4p111

A Consideration on Factors of Collecting Buying Behavior

2017· article· en· W2739916508 on OpenAlexvenueno aff
Arash Allahdini, Shahrzad Chitsaz, Hamid Saeedi

Bibliographic record

VenueInternational Journal of Marketing Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPossession (linguistics)Hoarding (animal behavior)Variety (cybernetics)Value (mathematics)Meaning (existential)Function (biology)MarketingPsychologyProcess (computing)AdvertisingSocial psychologyComputer scienceBusinessFeeding behaviorArtificial intelligence

Abstract

fetched live from OpenAlex

This paper deals with reviewing the literature on factors related to collecting behavior and considers individual, social and other impacts on collector’s life and functions during collecting. Variety of findings based on researches type such as researches on levels of possession, rareness, and value which influence on collecting behavior, and researches methodology are useful to consumer behavior science. Collecting has useful spiritual and mental effects and it is different from hoarding. Collectible things convey specific meanings. The process of collection completion is like child growth process in which the child starts with collecting cards or stones and then proceeds to demand more worthy things. There are different collecting behaviors in men and women. Things may have two functions; one is the real function to be used and the other is as a part of collecting. Collector is a person who is interested in a specific type of thing because of symbolic values to express oneself meaning, which do not mean hoarding.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.210
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.148
GPT teacher head0.367
Teacher spread0.219 · 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 teacher head, 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

Citations0
Published2017
Admission routes1
Has abstractyes

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