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Record W2888941412 · doi:10.5539/ijps.v10n3p95

A Psychometric Analysis of the Greek Career Adapt-Abilities Scale in University Students

2018· article· en· W2888941412 on OpenAlexvenueno aff
Despina Sidiropoulou-Dimakakou, Katerina Mikedaki, Katerina Argyropoulou, Andronikos Kaliris

Bibliographic record

VenueInternational Journal of Psychological Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisScale (ratio)Internal consistencyCuriosityConstruct validityTest (biology)Reliability (semiconductor)Convergent validityDimension (graph theory)Sample (material)Construct (python library)Social psychologyPsychometricsStructural equation modelingDevelopmental psychologyStatistics

Abstract

fetched live from OpenAlex

Based upon substantial research on career adaptability, and on specific cross-cultural validation research of the Career Adapt-abilities Scale (CAAS) (Savickas & Porfeli, 2012) we recruited a sample of Greek university students (Ν = 452) in order to test further the Greek form of the scale. Confirmatory Factor Analysis models showed that the four-factor structure was supported for the Greek form, comprising four dimensions: concern, control, curiosity, and confidence. The original six items per dimension structure was also maintained. Internal consistency estimates were satisfactory, and test-retest reliability reached acceptable levels. Indications of convergent validity were found as CAAS positively correlated with self-esteem. To further explore for the construct validity of the scale score differences by gender and year of studies were also examined. Overall, the observed differences were found to be in the expected direction. This validity study indicates that CAAS may be safely applied to the Greek students.

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 score0.012
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.131
GPT teacher head0.408
Teacher spread0.278 · 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
Published2018
Admission routes1
Has abstractyes

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