Pairing People with Products: Anthropomorphizing the Object, Dehumanizing the Person
Bibliographic record
Abstract
We present the first empirical integration of anthropomorphism and dehumanization, two intrinsically linked processes representing the extent to which the concept of humanness is activated for a given target. Across several experiments, we demonstrate that pairing a person and object in an ad, while focusing respondent attention on the object, leads to its being anthropomorphized and evaluated better compared to presenting it alone. However, compared to presenting a person alone, the same pairing leads to inferior evaluations of the person through a process of dehumanization. We rule out two alternative explanations for these effects, namely the transfer of an object's qualities to the person and consumption associations, and conduct a post‐test that provides additional support for our proposed activation/inhibition of humanness account. Finally, we inspect several moderators, finding that anthropomorphism only occurs with moderately and highly functional objects and dehumanization occurs irrespective of the person's gender or fame. By incorporating the literature on dehumanization, we propose new research questions to motivate future inquiry.
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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 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".