The Development of the Text Evaluation Scale for Child Rights: A Study of Validity and Reliability
Bibliographic record
Abstract
This study was conducted with the aim of developing The Text Evaluation Scale for Child Rights. There are fourdifferent sample chosen for the face validity, content validity and construct validity (for pilot scheme and main study)of the study. For face validity, a sample group of 3 experts chosen with the method of purposeful sampling includingthe researcher was formed. For content validity, snowball method was determined and studied with 12 experts. Forthe study of construct validity, random sampling method was performed for the sample selection in pilot studyinvolving 120 people and in main study involving 510 people.The theoretical framework of the scale was determined by means of the attempts, conventions, studies regarding thesubject basing upon the United Nations Organization Child Rights Convention and additional protocols to thisconvention. One could get minimum 40 and maximum 200 points from the five-point Likert scale which consists of28 positive and 12 negative (total 40) items. The scale has two sub-dimensions which are content and author. Thefact that Cronbach Alpha reliability coefficient is high regarding the sub-dimensions of the scale (authorsub-dimension= 0,822 content sub-dimension= 0,834) shows that the items in the sub-dimensions are consistent withone another. Cronbach Alpha value for the whole of the scale was determined as 0,90 which means that the scale ishighly reliable. Besides, in the scale, there are items of which factor loading value is higher than 0,45. When validityand reliability results are examined, it can be seen that the scale could be utilized to evaluate the text in terms ofbeing suitable for the child rights.
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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 | 0.026 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".