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Record W1593009786 · doi:10.1111/jopy.12151

Majoring in Selection, and Minoring in Socialization: The Role of the College Experience in Goal Change Post–High School

2014· article· en· W1593009786 on OpenAlexaff
Patrick L. Hill, Joshua J. Jackson, Nicole Nagy, Gabriel Nagy, Brent W. Roberts, Oliver Lüdtke, Ulrich Trautwein

Bibliographic record

VenueJournal of Personality · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologySocializationPerceptionSelection (genetic algorithm)GermanGoal orientationSocial psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Though it is frequently assumed that the college experience can influence our life goals, this claim has been relatively understudied. The current study examined the role of goals in college major selection, as well as whether major selection influences later goal change. In addition, we examined whether a person's perceptions of his or her peers' goals influence goal setting. Using a sample of German students (Mage = 19 years; n = 3,023 at Wave 1), we assessed life goal levels and changes from high school into college across three assessment occasions. Participants reported their current aspirations, along with the perceived goals of their peers during the college assessments. Using latent growth curve models, findings suggest that life goals upon entering college significantly predict the majors students select. However, this major selection had limited influence on later changes in life goals. Stronger effects were found with respect to perceptions of peers' goals, with students tending to change their goals to better align with their peers. The current study provides evidence that life goals are relatively stable and yet can change during the emerging adult years, in ways that demonstrate the potential influence of the college experience.

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 score0.009
Threshold uncertainty score0.357

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 studies0.0000.000
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 head0.029
GPT teacher head0.318
Teacher spread0.289 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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