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
This paper examines the rise of COVID-19 related conspiracy theories through a Durkheimian lens. Specifically, Durkheim’s concepts of anomie, collective consciousness, and religion can be useful in interpreting the increased participation in conspiracy theory groups. It examines how social distancing measures and government restrictions have led to increased anomie, and how conspiracy theory groups have been used to mitigate this anomic state by introducing shared beliefs and norms. These groups have also created opportunities for people to come together physically and virtually, sharing common beliefs and goals creating a distinct collective consciousness. This paper also focuses on social media’s role in perpetuating conspiracy theories and how online communities create an environment where it becomes difficult to decipher fact from fiction. It also focuses on how online communities foster group cohesion in a virtual environment. In addition, the paper also likens conspiracy groups to religious ones using Émile Durkheim’s definition.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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