Gender Differences and the Five Facets of Conspiracy Theory
Bibliographic record
Abstract
Although research examining conspiracy theory beliefs has been examined, there is conflicting literature on the relationship between gender and conspiracy thinking. Before this study, little research has been conducted on the differences between males and females in each of the five facets of conspiracy theory. This study was designed to investigate differences in gender as they pertain to government malfeasance (GM), malevolent global conspiracies (MG), extraterrestrial cover-up (ET), personal well-being (PW), and control of information (CI). It was hypothesized that there are statistically significant differences between females and males when it comes to conspiracy theory beliefs for each of the five facets. Archival data from 2016 containing responses to the Generic Conspiracist Beliefs Scale was analyzed. Results supported the main hypothesis of this investigation that significant differences do, in fact, exist between females and males in all five facets of conspiracy theory: government malfeasance, malevolent global conspiracies, extraterrestrial cover-up, personal well-being, and control of information. In addition, this study revealed that females score higher than males in all facets. In general, a computed total conspiracy belief score demonstrated that females (M = 45.10, SD = 15.07) were significantly higher than males (M = 42.13, SD = 15.90). Nevertheless, some recent research has reported that women were significantly less likely than men to engage in ‘conspiratorial thinking’ and endorse a conspiracy about the COVID-19 pandemic of 2020. These findings may be suggesting a change in direction for gender differences and a need for further research.   
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.
How this classification was reachedexpand
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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".