Opinions of Middle School Students on the Justice Concept within the Framework of Social Studies Education
Bibliographic record
Abstract
The aim of this study is to reveal the opinions of middle school students about the justice concept. The study was carried out in accordance with the document review technique, which is one of the qualitative research methods. The study group consists of 82 students attend in 7th grade receiving education at a middle school in the city of Kastamonu in the school year 2016-2017. Data was obtained using semi-structured interviews consisting of open-ended questions. This data was interpreted using content analysis and by way of coding. Middle school students’ opinions on justice concept are represented in 8 different categories and they use 7 different sayings relating to the justice concept. Whereas the justice concept is most often explained as “Rightfulness”, it is least often conceived as “Abstinence from Committing Crimes”. It is observed that the saying “Justice can do what swords cannot” is used by middle school students most often, and the saying “No merit can be more noble than justice” least often. In light of this information, middle school students can be provided with environments in which they can internalize the justice concept. Furthermore, results about justice can be drawn when its content is broadened. We can do scientific study about justice in more detail by increasing sample group.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".