AN ANALYSIS ON THE ANTI-VACCINATION MOVEMENT IN TURKISH DIGITAL PLATFORMS: EKŞİSÖZLÜK AND FACEBOOK
Bibliographic record
Abstract
The anti-vaccination movement turned into a public health problem also in Turkey. This paper analyzes the vaccine-related posts of one of the anti-vaccination group on Facebook. The group was selected as a “purposive sample”. Also, vaccine-related entries from EkşiSözlük, one of Turkey’s most popular collaborative hypertext dictionaries, were analyzed. The study aimed to find out if digital social media in Turkey were the main hub for the anti-vaccination movement, as this is the case in several countries, while also aiming to find out the motivations of anti-vaxxers. The Thematic Content Analysis (TCA) of Facebook messages and EkşiSözlük entries showed that Facebook appeared as a platform used more by anti-vaccination, mostly religious anti vaccination groups for disseminating their ideas. In contrast, very few anti-vaxxer messages were seen on EkşiSözlük, used by more secular and usually educated people. It was seen that anti-vaxxers were motivated by postmodern allegedly “scientific” and religious arguments, both of which are often shaped by conspiracy thinking.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".