Evolutionary neuromarketing: darwinizing the neuroimaging paradigm for consumer behavior
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
Abstract The current paper serves two purposes. First, it reviews the neuroimaging literature most relevant to the field of marketing (e.g., neuroeconomics, decision neuroscience, and neuromarketing). Second, it posits that evolutionary theory is a consilient and organizing meta‐theoretical framework for neuromarketing research. The great majority of neuroimaging studies suffer from the illusion of explanatory depth namely the sophistication of the neuroimaging technologies provides a semblance of profundity to the reaped knowledge, which is otherwise largely disjointed and atheoretical. Evolutionary theory resolves this conundrum by recognizing that the human mind has evolved via the processes of natural and sexual selection. Hence, in order to provide a complete understanding of any given neuromarketing phenomenon requires that it be tackled at both the proximate level (as is currently the case) and the ultimate level (i.e., understanding the adaptive reason that would generate a particular neural activation pattern). Evolutionary psychology posits that the human mind consists of a set of domain‐specific computational systems that have evolved to solve recurring adaptive problems. Accordingly, rather than viewing the human mind as a general‐purpose domain‐independent organ, evolutionary cognitive neuroscientists recognize that many neural activation patterns are instantiations of evolved computational systems in evolutionarily relevant domains such as survival, mating, kin selection, and reciprocity. As such, an evolutionary neuromarketing approach recognizes that the neural activation patterns associated with numerous marketing‐related phenomena can be mapped onto the latter Darwinian modules thus providing a unifying meta‐theory for this budding discipline. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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