Evaluating the psychometric properties of the Five Factor Machiavellianism Inventory in a Canadian Sample
Bibliographic record
Abstract
3.1. The Five Factor Machiavellianism Inventory (FFMI) is a 52-item self-report questionnaire that measures the construct of Machiavellianism. Those who score high in Machiavellianism are said to be callous, manipulative, planful, and status-driven, and use manipulation and antagonism strategically in order to achieve status and desired goals. (Christie & Geis, 1970; Collison et al., 2018). Each item corresponds to one of 13 subscales, and each subscale corresponds to one of three factors: antagonism (e.g., manipulation, cynicism), planfulness (i.e., deliberation, order), and agency (e.g., assertiveness, achievement). The FFMI resolves a key limitation of previous measures of Machiavellianism, as the FFMI was designed to be distinct from psychopathy. However, the psychometric properties of this scale have not been investigated in a Canadian Sample. In addition, previous studies confirmed the structure of the scale using exploratory structure equation modelling, so its factor structure has not been examined using a traditional confirmatory factor analysis approach. Therefore, the goal of this study was to evaluate the psychometric properties of the FFMI using traditional confirmatory factor analysis and exploratory structural equation modelling.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.013 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.011 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".