Bibliographic record
Abstract
U radu su predstavljeni rezultati kvantitativne studije koja je istraživala ponašanje studenata Beogradskog univerziteta u vezi sa kupovinom knjiga koje ne spadaju u domen nastavne literature. U elektronskom anketiranju sprovedenom u julu 2020. godine učestvovao je 471 ispitanik čiji su se odgovori odnosili na ponašanje u proteklih godinu dana. Rezultati pokazuju da je čak 84,3% (397) akademaca kupilo barem jednu knjigu tokom navedenog perioda. Najčešće se knjige nabavljaju u nekom od lanaca knjižara (332), mada nije zanemarljiv broj onih koji ih naručuju sa veb-sajtova knjižara (157) ili na nekim drugim veb-stranicama (86). Određen broj studenata kupuje i elektronske knjige (33). Ispitanici se najčešće odlučuju za klasike iako su zainteresovani i za trilere, drame, kriminalističke romane, kao i za edukativne sadržaje, filozofiju i psihologiju. Polovina studenata koji kupuju knjige pozajmljuje štivo za čitanje iz biblioteke. Od onih koji knjige ne kupuju, 23% (17) koristi usluge biblioteka, a 27% (20) njih čita knjige u elektronskom obliku koje pronalazi na internetu.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".