Bibliographic record
Abstract
With as of the start of the 2000s, technology and internet have become almost indispensable in the lives of individuals. Rapid development of technology has increased the interest and dependence of people on the internet and made it compulsory to use the internet. Increased use of the internet has led to the development invention of mobile devices, cloud technologies, and information and communication technologies. Besides facilitating and accelerating their lives, this situation has caused individuals to encounter some risks. Individuals can exchange information in an online environment, share their feelings and thoughts in a comfortable way, easily benefit from public services and be aware of the events that take place in various parts of the world. In addition, they have started to perform some transactions in electronic media such as e-shopping, e-government, e-book, e-library, e-pulse, e-banking. This brought about the concept of digital life. Digital life has changed a large part of our habits as the Internet began to enter our lives. Most of these changes are in the fields of communication and life perception. This phenomenon led researchers to work more intensively on the concept of digital citizenship. While researching the effects of digital citizenship on the one hand, studies were carried out to determine what to do at school and at teachers’ level. The aim of this study is to address the trends and gaps observed in the research studies about on digital citizenship and to focus on which their subject areas in Turkey. As a result of literature review: (1) Most of the researches studies that are conducted as a result of literature review are focused on students and teachers, (2) In these studies many different scales have been developed to determine the levels of digital citizenship according to the focal point and different factors.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".