The Consuming Instinct: What Darwinian consumption reveals about human nature
Bibliographic record
Abstract
Editor's Note. In this engaging talk given last February on a particularly cold and blustery day at Texas Tech University, Professor Gad Saad of Concordia University discusses his work in the area of evolutionary consumption. In making the case for understanding consumerism from a Darwinian perspective, Saad addresses several key tenets from his books The Consuming Instinct and The Evolutionary Bases of Consumption . In particular, Saad argues that: (1) many consumption acts can be mapped onto four key Darwinian modules (survival, mating, kin selection, and reciprocal altruism); and, (2) cultural products such as song lyrics and movie plotlines are fossils of the human mind that highlight a shared, biologically based human nature. In this wide-ranging inquiry, Saad summarizes several of his other empirical works, including the effects of conspicuous consumption on men's testosterone levels and how the ovulatory cycle in the human female influences consumption. Overall, Professor Saad contends that an infusion of evolutionary and biologically based perspectives into the discipline of consumer behavior and related government regulatory policies yields myriad benefits, notably greater consilience, more effective practices, an ethos of interdisciplinarity, and methodological pluralism.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".