Examining The Quarter-Life Crisis of Library Science Students at UIN Sunan Kalijaga Yogyakarta Through Digital Literacy Impact
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rapid digital advancements present opportunities and challenges that significantly affect young adults' mental and emotional well-being. This study aims to 1) determine the level of digital literacy of UIN Sunan Kalijaga Library Science students, 2) determine the level of quarter-life crisis experienced by UIN Sunan Kalijaga Library Science students, and 3) determine the effect of digital literacy skills on quarter life crisis of UIN Sunan Kalijaga Library Science students. This research uses quantitative methods with descriptive and correlation types. The subjects are Library Science students’ classes of 2019 and 2020, and the object is the influence of digital literacy on the quarter-life crisis. Data collection was carried out using interview techniques, documentation, and questionnaires. Data were analyzed using mean, grand mean, product-moment correlation, and simple linear regression. The results of the analysis show that 1) students' digital literacy is in a very high category with a value of 3.4, 2) students experience a quarter-life crisis of 2.85 in the high category, and 3) digital literacy affects quarter-life crisis with a significance value of 0.000 <0.05. Based on the coefficient of determination, digital literacy affects 18.4% of quarter-life crises. Product moment correlation analysis shows a Pearson correlation value of -0.429, which means the higher the digital literacy, the lower the quarter-life crisis, and vice versa.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.003 | 0.001 |
| 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 it