Replication Data for: Some people just want to watch the world burn: The prevalence, psychology and politics of the “Need for Chaos
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 replication zipped folder contains the following: 1) A Folder Called "Cutstatadatasets_codebooks_ with Stata v.12 datasets with the set of variables for each of the four nations a) Australia; b) Canada; c) United Kingdom; and d) United States and codebook entries for relevant variables 2) A Folder Called "MainRFiles" which reads the stata .dta files and produces output files for Mplus and (after the profiles generated by the LPA runs in Mplus) estimates the multvariate estimations in the paper 3) A Folder Called LatentProfilesfromMplus which contains the profiles generated by Mplus that should be appended to the data for use in the multivariate estimations 4) A Folder Called Tables 1_2: Mplus files that generate the laten profile analyses in the paper 5) A Folder Called AppendixCFA_Chaos: The final Confirmatory Factor Analysis and steps taken to obtain the final CFA--all Mplus outputs, with core data files generated by R available 6) A Folder Called AppendixEFA: The Exploratory Factor Analyses from Mplus establishing that the Need for Chaos is Distinct from the Dark Triad
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 | 0.001 |
| 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 | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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