Do political and economic decision-making rely on common neural substrates?
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
The methods of cognitive neuroscience have begun to be applied to study political behavior. The neural substrates of value-based choice have already been extensively studied in economic contexts, and might provide a powerful starting point for understanding political choice. In this thesis, I present work that addresses the commonalities and distinctions between political and economic choice, within a cognitive neuroscience framework. First, a systematic literature review was undertaken to identify papers reporting neural correlates of political behavior in humans. We then asked whether the brain regions linked to subjective value in economic choice were engaged during political choice, addressing this question with a functional magnetic resonance imaging meta-analysis. This showed that only a small number of studies of political behavior have used frameworks that are comparable to those used in neuroeconomics. Further, few of the activation foci reported in these studies of political behavior fell within areas consistently found to reflect subjective value in economic studies. This raised the interesting possibility that the neural substrates of subjective value identified in economic choice paradigms may not generalize to political choice, but also highlighted the need for political choice paradigms that would allow this question to be directly tested.As a first step in this direction, in a second study we adapted a task commonly used to study information gathering in economic choice to study hypothetical voting choices. We asked whether this methodology could be applied to measure evidence gathering in voting and explored the effect of partisanship on this process. Twelve Canadian Liberal partisans and twelve non-partisans made binary choices between photographs of unknown political candidates in the presence and absence of party information, while choice behavior and eye movements were measured. In the absence of party information, we found that choice behavior and eye movement patterns across groups resembled those found in economic choice studies, but partisans trended toward faster choices and made significantly fewer fixations. When party information was introduced, both groups still conformed to choice behavior and eye movement patterns consistent with those seen in economic paradigms. Although party information had a substantial effect on voting behavior and eye movements in partisans, it did not completely supersede the effects of visual information and attentional modulation present throughout a trial as would have been expected if choices were being made purely based on party information. Preliminary efforts to fit an existing computational model developed in economic choice showed that partisans’ behavior was consistent with a lowered decision threshold, and party information acted to boost the initial value of the option for partisans. This work suggests that binary choice tasks used in economic studies can be applied to analyze political decisions, and provides preliminary data on the mechanisms by which partisanship influences such choices. This thesis provides a starting point for a neuroscience-informed analysis of political decision-making behaviors, and sets the stage for work to address the neural basis of these behaviors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it