The Influence Strategies of Interviewees Suspected of Controlling or Coercive Behavior
Bibliographic record
Abstract
This research examines how suspects attempt to influence interviewers during investigative interviews. Twenty-nine interview transcripts with suspects accused of controlling or coercive behavior within intimate relationships were submitted to a thematic analysis to build a taxonomy of influence behavior. The analysis classified 18 unique suspect behaviors: the most common behaviors were using logical arguments (17% of all observed behaviors), denial or denigration of the victim (12%), denial or minimization of injury (8%), complete denials (7%), and supplication (6%). Suspects’ influence behaviors were mapped along two dimensions: power, ranging from low (behaviors used to alleviate investigative pressure) to high (behaviors used to assert authority), and interpersonal alignment, ranging from instrumental (behaviors that relate directly to evidence) to relational (behaviors used to bias interviewer perceptions of people and evidence). Proximity analysis was used to examine co-occurrence of influence behaviors. This analysis highlighted combinations of influence behaviors that illustrate how different behaviors map onto different motives, for example shifting attributions from internal to external to the suspect, or to use admissions strategically alongside denials to mitigate more serious aspects of an allegation. Our findings draw together current theory to provide a framework for understanding suspect influence behaviors in interviews.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".