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Record W2340858263

GLOBAL VILLAGE OR URBAN JUNGLE: CULTURE, SELF-CONSTRUAL, AND THE INTERNET

2000· article· en· W2340858263 on OpenAlexaff
Stephen Biggs

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsYork University
Fundersnot available
KeywordsCollectivismInterdependenceIndividualismJungleSociologyThe InternetSocial psychologySelf construalContext (archaeology)GeographyPsychologySocial sciencePolitical scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Cultural psychologists have known for some time that self-perception or self-construal is mediated in large measure by cultural boundaries and structures like geography: for example, that agrarian and collectivist cultures are more interdependent than so-called Western or individualistic cultures. Mod-ern communication technologies like the Internet are blurring the distinctions between cultures and tearing down geographic boundaries, creating questions about the implications for the psychology of self. In this paper are addressed the psychological implications of the global network as a cultural context and whether the Internet promotes an individualistic or interdependent sense of self. T IS a safe assertion that modern communication technologies like the Internet have the poten-tial to tear down geographic boundaries and blur the distinctions between what have been thought of as traditional cultures. So what are the implications for those cultures and the indi-viduals therein? What are the implications for the psychology of self? In this paper I would like to address the psychological implications of the global network as a cultural context and whether the Internet promotes an individualistic or interdependent sense of self. This paper is an attempt to sort out a number of ideas in preparation for an empirical study of the relationship between self-construal, culture, and Internet use. I will begin with a cursory examination of current Inter-

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.971

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)0.0290.000

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 head0.033
GPT teacher head0.325
Teacher spread0.293 · 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.

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

Citations8
Published2000
Admission routes1
Has abstractyes

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