Moral Reasoning and Its Connections With Machiavellianism and Authoritarianism: The Critical Roles of Index Choice and Utilization
Bibliographic record
Abstract
Moral reasoning typically relates unexpectedly weakly with both Machiavellianism and authoritarianism. Although researchers often explain this by pointing to apparent shortcomings in both the construct and the measure of moral reasoning, such explanations are questionable given the many instances of support for hypotheses involving moral reasoning using the same construct and measure. As these latter cannot only sometimes be flawed, we explored the possible influence of moral reasoning index choice on observed results by using multiple indices available in the Defining Issues Test (DIT). In a sample of 201 employed persons surveyed in 1998, with results reported for the first time, advanced moral reasoners tended to be neither Machiavellian nor authoritarian. However, the specific moral reasoning index employed was critical to detecting these hypothesized inverse relationships. Specifically, we proposed (and determined) that currently unavailable D scores would be the relevant index for examining inverse relationships with Machiavellianism and that P scores would be most appropriate in the context of inverse relationships with authoritarianism, particularly among persons inclined to utilize their characteristic moral reasoning (assessed with U scores). We extrapolate the conceptual logic underpinning such relationships, and suggest that appropriate index choice flows from this logic and is essential to hypothesis testing across a broad array of constructs. Future research could adopt this logic to examine relationships involving constructs with implications similar to those found in Machiavellianism and authoritarianism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.133 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".