UTICAJ DRUŠTVENIH MREŽA NA UNAPREĐENJE SVIJESTI O ZDRAVLJU I SPORTSKOJ AKTIVNOSTI MLAĐE POPULACIJE
Bibliographic record
Abstract
Društvene mreže predstavljaju jednu od najzastupljenijih digitalnih tehnologija u BiH danas, a kao medij bilježi najveći stepen rasta u odnosu na tradicionalne medije. Putem društvenih mreža korisnici razmjenjuju svoje stavove i mišljenja, ali i formiraju nove norme ponašanja i utiču na javnost generalno. Uticaj društvenih medija na mlađu populaciju trenutno predstavlja fokus šire društvene javnosti. Cilj ovog istraživanja je da se utvrdi da li društvene mreže imaju pozitivan uticaj na ponašanje i navike mlađe populacije, koji su i najčešći korisnici društvenih mreža. Konkretno, istraživanje ima za cilj da se otkrije da li njihovo korištenje ima pozitivne implikacije na unapređenje svijesti o zdravlju kroz korištenje online platformi, aplikacija ili ostalog online sadržaja među populacijom koja već na neki način brine o svom zdravlju putem rekreativnih sportskih aktivnosti. Svrha ovog istraživanja je da se dođe do novih saznanja kada je u pitanju uticaj društvenih mreža na obrazovanje i brigu o zdravlju mlađe populacije.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.005 |
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".