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Record W2272376886 · doi:10.1177/2167696815601945

Figures of Admiration in Emerging Adulthood

2015· article· en· W2272376886 on OpenAlexaff
Oliver Robinson, Abby Dunn, Sofya Nartova‐Bochaver, Константин Бочавер, Samaneh Asadi, Zohreh Khosravi, Seyed Mohammad Jafari, Xiaozhou Zhang, Yanbo Yang

Bibliographic record

VenueEmerging Adulthood · 2015
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAdmirationGenerativityPsychologyAssertivenessChinaDevelopmental psychologySpiritualityFormative assessmentThematic analysisAutonomyGender studiesSocial psychologyQualitative researchSociologySocial scienceHistoryMedicinePolitical science

Abstract

fetched live from OpenAlex

Admiration is a social emotion that is developmentally formative in emerging adulthood; admired adults act as mentors, role models, and sources of inspiration to this age-group. The present study explored who and what emerging adults admire in their elders, across four countries (UK, Iran, China, and Russia). A total of 525 participants provided written descriptions of an admired figure. Across all cultures, care and generativity was the most common theme. Cross-cultural differences emerged for the themes of limitations and difficulties (most prevalent in China), autonomy and assertiveness (most prevalent in Russia), intellect and education (most prevalent in Russia), and religion and spirituality (most prevalent in Iran). Males and females in the UK and Russia tended to select admired figures of their own sex, but in Iran and China both male and female participants selected more male than female figures. The findings suggest a common thematic core to admiration in emerging adulthood combined with culturally specific features.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
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 head0.037
GPT teacher head0.343
Teacher spread0.306 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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