Bibliographic record
Abstract
Citizenship has become one of the important topics discussed in especially developed countries by policy makers and various stakeholders in recent years. Some important reasons behind it are the political, economic and social uneasiness throughout the world in both collectivistic and individualistic societies. The current study aims at looking at the citizenship perception among university students in one of those collectivistic countries. The participants answered the question ‘what does citizenship mean for you?’ and the data was analyzed by giving descriptive statistics using the quantitative data analysis software, SPSS. The value items given as choices to the students were; equality, freedom, social order, national security, a world at peace, respect for tradition, respect for privacy, social justice, independent, protecting the environment, loyalty, obedient, helpful, and responsible. The participants were categorized in two different faculties which were faculty of humanities and social sciences and faculty of management and administrative sciences. The results show that the students from faculty of humanities and social sciences have tendency towards values represented in individualistic societies while defining citizenship. On the other hand, students of faculty of management and administrative sciences showed greater tendency towards the values represented in collectivistic countries. Another finding of the study was that females highly prioritized all value items compared to male participants. Turkey is considered to be a collectivistic country however the results show that majority of the participants prioritize values represented in individualistic nations. Further studies need to be conducted in order to find out whether there has been a shift from being a collectivistic society or not.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".