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Record W2766472565 · doi:10.5964/ijpr.v11i1.223

Function of Attachment Hierarchies in Young Adults Experiencing the Transition From University

2017· article· en· W2766472565 on OpenAlexafffund
Elaine Scharfe, Robyn Pitman, Valerie Cole

Bibliographic record

VenueInterpersona An International Journal on Personal Relationships · 2017
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of GuelphTrent University
FundersTrent University
KeywordsPsychologyCornerstoneAttachment theoryDevelopmental psychologyDistressHierarchyLongitudinal studySocial psychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

An important cornerstone of Bowlby’s attachment theory (1969/1997) is the proposal that moving away from parents and toward peers is an indication of healthy development. In this study, we explored the benefit of the shift, not the shift itself, in a sample of emerging adults experiencing a stressful life event (i.e., the transition from university). Although the shift from parents to peers is an important cornerstone of Bowlby’s theory, this study is one of the first to test the differential effects of parent and peer networks on adjustment. In this longitudinal study, 73 participants completed surveys to assess attachment, social networks, and distress one month before completing their undergraduate degree and 6 months later. We found that participants experiencing the transition from university, who chose a peer as the first person in their network, tended to report stable scores over time whereas participants who chose a family member reported more variable scores. Interestingly, the direction of change was not different for the groups, just the magnitude of change. Furthermore, the difference in adjustment was not found when we compared the groups using the percent hierarchy method highlighting that there is a benefit of exploring primary attachment relationships when examining the influence of networks on adjustment.

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)0.000
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 score0.163
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.359
Teacher spread0.319 · 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

Citations6
Published2017
Admission routes2
Has abstractyes

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