Conspiracy theories and their truth trajectories
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 article aims to reinvigorate analytical debates on conspiracy theories. It argues that definitional attempts to set conspiracy theories apart from other theories are flawed. Blinded by the “irrational” reputation of conspiracy theories and deluded by the workings of institutionalized power such approaches fail to recognize that there are no inherent differences between the two categories. We argue that assessments of conspiracy theories should focus not on the epistemological qualities of these theories but on their interactions with the socio-political fields through which they travel. Because “conspiracy theory” is not a neutral term but a powerful label, attention to processes of labeling highlights these larger fields of power, while the theories’ trajectories illuminate the mechanisms by which truth and untruth are created. As such, this article offers a way forward for assessing both the truth and use value of conspiracy theories in the contemporary world.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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