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Record W2612117193 · doi:10.1080/15298868.2017.1327453

Longitudinal directive effect of need satisfaction in self-defining memories on friend related identity processing styles and friend satisfaction

2017· article· en· W2612117193 on OpenAlexafffund
Nabil Bouizegarene, Frédérick L. Philippe

Bibliographic record

VenueSelf and Identity · 2017
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyIdentity (music)FriendshipSocial psychologyAutonomyDirectiveCompetence (human resources)Developmental psychologyComputer science

Abstract

fetched live from OpenAlex

Research suggests that identity and memory are deeply interconnected, but little is known about the identity processes and the memory characteristics involved in this interaction. We employed a longitudinal design to examine relations between the satisfaction of autonomy, relatedness, and competence needs in self-defining memories and identity processing styles within the domain of friendship. We also assessed satisfaction with friends to evaluate the relation of identity processes and memory characteristics to well-being in friendships. Participants were 166 students who responded twice (at about a two-year interval) to the Identity processing style Inventory-3 and the Satisfaction with Life Scale. We adapted these measures to tap into the domain of friendships, which is an important aspect of young adults’ identity. Participants also described a friend-related self-defining memory and rated the degree of need satisfaction they experienced in that event. A cross-lagged panel analysis revealed that memory need satisfaction predicted increases in informational identity processing style and friend satisfaction over time. Implications for the directive function of memory in identity are discussed.

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)0.007
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.012
GPT teacher head0.326
Teacher spread0.314 · 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

Citations12
Published2017
Admission routes2
Has abstractyes

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