Turkish Adaptation of the Children’s Anger Scale: Reliability and Validity Analyses
Bibliographic record
Abstract
This study aims to establish a Turkish version of the Children’s Inventory of Anger Scale (ChIA) developed by Nelson and Finch (2000) to evaluate the intensity of anger experienced in potentially anger-provoking situations in children. The research sample consists of 502 primary and secondary school students attending their education in Hatay province of Turkiye. In the study, the construct validity of the ChIA, correlations of subscales with each other, criterion relative validity, Cronbach’s alpha internal consistency, item-total score correlation, and test-retest reliability coefficients were examined. As a result of the confirmatory factor analysis performed for the construct validity of the scale, it was observed that the ChIA was compatible in four sub-dimensions as in the original scale and all items were placed in the relevant sub-scale. In addition, Cronbach’s alpha coefficient of the ChIA was found to be .87, .78, .82, .75, and .81 for the sub-scales of inhibition, physical aggression, peer relations, and authority relations, respectively; test-retest consistency was found to be .83, .80, .82, .87 and .81 for inhibition, physical aggression, peer relations, and authority subscales, respectively. Statistical analyses of the ChIA have shown that it is a valid and reliable scale that can be used to measure the expression of anger and the impact of anger on personal relationships while assessing specific situations that cause anger in children aged 8-11 years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".