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Record W1988787971 · doi:10.2466/pr0.94.3.995-1008

Do Human Values Reflect Job Decisions and Prosocial and Antisocial Behavior? A Contribution towards Validating the Austrian Value Questionnaire by Group Comparisons

2004· article· en· W1988787971 on OpenAlexaboutno aff
Ingrid Salem, Walter Renner

Bibliographic record

VenuePsychological Reports · 2004
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyReligiosityProsocial behaviorSocial psychologyConstruct validityConstruct (python library)Developmental psychologyPsychometrics

Abstract

fetched live from OpenAlex

The Austrian Value Questionnaire was developed on the basis of the Lexical Approach to account for specific facets of values in Austrian culture. It comprises 54 items, constituting five scales, Intellectualism, Harmony, Religiosity, Materialism, and Conservatism, and 13 subscales. To assess construct validity, hypotheses on human values were derived from the literature and tested in Austrian samples of Catholic priests and nuns (n=30, 8 women, M age=52.6 yr.), community servants (n=30, all men, M age=21.4 yr.), and students of psychology (n=33, 19 women, M age=23.8 yr.) and economics (n=33, 18 women, M age=23.8 yr.), prisoners (n=40, 9 women, M age=34.9 yr.), and drivers who had been fined for driving while intoxicated (n=35, 5 women, M age=34.6 yr.). Participants were volunteers. Previous and more recent findings from the USA, Canada, Germany, and Switzerland provided similar results for community servants, students of economics, prisoners, and intoxicated drivers, and thus, the hypotheses for these groups were largely confirmed. Most earlier findings for priests and nuns and students of psychology were not replicated, however. Taking into account that values may change over time and variously in different cultures, the results pose an argument for the construct validity of the newly developed questionnaire.

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)0.001
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 score0.144
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.137
GPT teacher head0.460
Teacher spread0.324 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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