A day at a beach with a starfish man: Anthropomorphization of a cartoon starfish
Bibliographic record
Abstract
Anthropomorphization is the process by which humans ascribe human form or attributes to non-human animals or objects. A recent study revealed that people anthropomorphized a cartoon starfish more strongly when the starfish had a face, than when the starfish did not have a face. Two experiments were conducted to determine if anthropomorphization of a cartoon, non-human animal (a starfish) occurs when: 1) visual elements associated with humans, such as clothing, were presented on the body, and 2) people read a story about the non-human cartoon character performing human activities. Participants completed body-part compatibility tasks in which they responded (thumb-press or foot-pedal) to a red or blue target (relevant feature) superimposed over the upper or lower limb (irrelevant feature) of a cartoon starfish, respectively. Experiment 1 consisted of two main presentation conditions: a starfish with a shirt and pants, and a starfish without clothing. Experiment 2 presented a starfish figure (without clothing) before and after participants read a story in which the starfish character went to the beach. Analysis of the RTs revealed body-part compatibility effects. Interestingly, the clothing and the story did not significantly modulate (increase) the magnitude of the compatibility effects. A possible explanation for such results could be that the pattern observed in both of the present experiments may be due to spatial compatibility rather than body-part compatibility effects. Alternatively, because the starfish did not have a face, the data from the series of experiments suggests that facial feature might be the key factor in facilitating anthropomorphization.Acknowledgments: This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".