Vulnerability to misinformation and Covid-19 infodemic in French-speaking Belgium (French version)
Bibliographic record
Abstract
The main objective of this report is to test the hypothesis that the adoption of an active information-seeking practice related to the health crisis on social networks can be understood as a risk practice in the Covid-19 infodemic. A second objective is to identify the existence of different vulnerability profiles in the infodemic and to understand the information practices associated with these different profiles at risk of misinformation. The approach adopted is therefore firstly a comparative approach between different types of profile. It is not a question of carrying out a longitudinal study representative of the evolution of the French-speaking Belgian population's experience of the crisis. The CoviCom survey is a four-wave questionnaire survey that was conducted in French-speaking Belgium between 30 March 2020 (i.e. 12 days after the entry into force of the first containment in Belgium) and 29 March 2021. In total, the survey collected 10,148 responses to the four waves of the survey (April 2020 containment, May 2020 decontainment, November 2020 second wave epidemic and March 2021 third wave epidemic).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".