Summary

This study was a preregistered replication of a prior CogSci study, with book covers removed and statements in randomized order.

We replicated our prior findings where hearing generic statements about a novel social group increased the inferred inductive potential of the group (relative to baseline), while hearing specific statements decreased inductive potential.

Methods

Participants

Data was collected from 452 adults via Prolific on Monday 4/21/26 - Tuesday 4/22/2026. Participants required to be in the United States, fluent in English, and having not participated in prior studies under this protocol. Participants were paid $2.00 for an estimated 8 minute task.

condition n
generic 147
baseline 152
specific 145

Exclusion criteria

We recruited 450 participants (150 per condition). Of those participants, 8 (1.8%) were excluded for meeting at least 1 of the following exclusion criteria:

  • failing the attention check (i.e., did not select 100% on slider when asked to during induction task) (n = 6 participants)

  • admitting to use of AI after being explicitly informed use was prohibited (n = 4 participants)

  • failing the task check (n = 1 participants)

Participants who failed the sound check were included, since a few participants mentioned technical difficulties with the Qualtrics automatically progressing past that video.

Demographics

We used the Prolific representative sample feature to recruit a sample representative on sex, age, and ethnicity (simplified US Census categories).

age
mean sd n
45.42 16.06 444
  • The sample skewed young in age.
gender n prop
Female 225 50.7%
Male 209 47.1%
Non-binary 6 1.4%
Prefer not to specify 2 0.5%
Genderqueer 1 0.2%
really sick of scoail construct of gender. I am who i am and like what i like. i refuse to participate for any team... 1 0.2%
  • The sample reflected the diversity of the gender identities in the US.
race n prop
White, Caucasian, or European American 271 61.0%
Black or African American 51 11.5%
Hispanic or Latino/a 35 7.9%
East Asian 13 2.9%
South or Southeast Asian 12 2.7%
White, Caucasian, or European American,Hispanic or Latino/a 7 1.6%
White, Caucasian, or European American,Native American, American Indian, or Alaska Native 7 1.6%
Middle Eastern or North African 5 1.1%
Native American, American Indian, or Alaska Native 5 1.1%
White, Caucasian, or European American,South or Southeast Asian 5 1.1%
Prefer not to specify 4 0.9%
White, Caucasian, or European American,Black or African American 3 0.7%
South or Southeast Asian,East Asian 2 0.5%
White, Caucasian, or European American,Black or African American,Native American, American Indian, or Alaska Native 2 0.5%
White, Caucasian, or European American,East Asian 2 0.5%
White, Caucasian, or European American,Hispanic or Latino/a,Black or African American 2 0.5%
White, Caucasian, or European American,Hispanic or Latino/a,Native American, American Indian, or Alaska Native 2 0.5%
White, Caucasian, or European American,Middle Eastern or North African 2 0.5%
Black or African American,Native American, American Indian, or Alaska Native 1 0.2%
Cape Verdean 1 0.2%
European American 1 0.2%
HUMAN RACE 1 0.2%
Hispanic or Latino/a,Black or African American 1 0.2%
Hispanic or Latino/a,Black or African American,Native American, American Indian, or Alaska Native 1 0.2%
Hispanic or Latino/a,East Asian 1 0.2%
Mixed 1 0.2%
Multi-race 1 0.2%
Native Hawaiian or other Pacific Islander 1 0.2%
White, Caucasian, or European American,Black or African American,East Asian 1 0.2%
White, Caucasian, or European American,Native American, American Indian, or Alaska Native,East Asian 1 0.2%
White, Caucasian, or European American,Native Hawaiian or other Pacific Islander 1 0.2%
mixed race 1 0.2%
  • The sample was also racially diverse, with White Americans slightly overrepresented and Hispanic Americans undererepresented.
education n prop
Less than high school 4 0.9%
High school/GED 62 14.0%
Some college 114 25.7%
Bachelor's (B.A., B.S.) 180 40.5%
Master's (M.A., M.S.) 62 14.0%
Doctoral (Ph.D., J.D., M.D.) 18 4.1%
Prefer not to specify 4 0.9%
  • A slight majority of the sample had completed at least a college education.

Behavioral analyses

Large circles with bars indicate means with 95% confidence intervals. Small dots indicate individual trial-level responses.

## Analysis of Deviance Table (Type II Wald chisquare tests)
## 
## Response: prevalence
##            Chisq Df            Pr(>Chisq)    
## condition 82.747  2 < 0.00000000000000022 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##  contrast            estimate    SE  df z.ratio p.value
##  generic - baseline     0.573 0.107 Inf   5.383 <0.0001
##  generic - specific     0.976 0.108 Inf   9.045 <0.0001
##  baseline - specific    0.402 0.107 Inf   3.764  0.0002
## 
## Results are given on the log odds ratio (not the response) scale.

As predicted, participants gave different prevalence estimates in the different conditions (Chisq(2) = 82.75, p < .001).

Specifically, participants in the generic condition inferred higher prevalence of test features than participants in the baseline condition (z = 5.38, p < .001), while participants in the specific condition inferred lower prevalence of test features than participants in the baseline condition (z = 3.76, p < .001).

Model comparison

Footnotes

## R version 4.5.2 (2025-10-31)
## Platform: aarch64-apple-darwin20
## Running under: macOS Tahoe 26.3
## 
## Matrix products: default
## BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## time zone: America/Los_Angeles
## tzcode source: internal
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] emmeans_2.0.1   car_3.1-3       carData_3.0-5   glmmTMB_1.1.14 
##  [5] lubridate_1.9.4 forcats_1.0.1   stringr_1.6.0   dplyr_1.1.4    
##  [9] purrr_1.2.1     readr_2.1.6     tidyr_1.3.2     tibble_3.3.1   
## [13] ggplot2_4.0.1   tidyverse_2.0.0 gt_1.3.0        scales_1.4.0   
## [17] janitor_2.2.1   here_1.0.2     
## 
## loaded via a namespace (and not attached):
##  [1] Rdpack_2.6.5        gridExtra_2.3       sandwich_3.1-1     
##  [4] rlang_1.1.7         magrittr_2.0.4      multcomp_1.4-29    
##  [7] snakecase_0.11.1    otel_0.2.0          compiler_4.5.2     
## [10] mgcv_1.9-4          systemfonts_1.3.1   vctrs_0.7.1        
## [13] pkgconfig_2.0.3     crayon_1.5.3        fastmap_1.2.0      
## [16] backports_1.5.0     labeling_0.4.3      rmarkdown_2.30     
## [19] tzdb_0.5.0          nloptr_2.2.1        ragg_1.5.0         
## [22] bit_4.6.0           xfun_0.56           cachem_1.1.0       
## [25] jsonlite_2.0.0      parallel_4.5.2      cluster_2.1.8.1    
## [28] R6_2.6.1            bslib_0.10.0        stringi_1.8.7      
## [31] RColorBrewer_1.1-3  boot_1.3-32         rpart_4.1.24       
## [34] jquerylib_0.1.4     numDeriv_2016.8-1.1 estimability_1.5.1 
## [37] Rcpp_1.1.1          knitr_1.51          zoo_1.8-15         
## [40] base64enc_0.1-3     Matrix_1.7-4        splines_4.5.2      
## [43] nnet_7.3-20         timechange_0.3.0    tidyselect_1.2.1   
## [46] rstudioapi_0.18.0   abind_1.4-8         yaml_2.3.12        
## [49] TMB_1.9.19          codetools_0.2-20    lattice_0.22-7     
## [52] withr_3.0.2         S7_0.2.1            coda_0.19-4.1      
## [55] evaluate_1.0.5      foreign_0.8-90      survival_3.8-6     
## [58] xml2_1.5.2          pillar_1.11.1       checkmate_2.3.3    
## [61] reformulas_0.4.3.1  generics_0.1.4      vroom_1.6.7        
## [64] rprojroot_2.1.1     hms_1.1.4           minqa_1.2.8        
## [67] xtable_1.8-4        glue_1.8.0          Hmisc_5.2-5        
## [70] tools_4.5.2         data.table_1.18.0   lme4_1.1-38        
## [73] fs_1.6.6            mvtnorm_1.3-3       rbibutils_2.4.1    
## [76] colorspace_2.1-2    nlme_3.1-168        htmlTable_2.4.3    
## [79] Formula_1.2-5       cli_3.6.5           textshaping_1.0.4  
## [82] ggthemes_5.2.0      gtable_0.3.6        sass_0.4.10        
## [85] digest_0.6.39       TH.data_1.1-5       htmlwidgets_1.6.4  
## [88] farver_2.1.2        htmltools_0.5.9     lifecycle_1.0.5    
## [91] bit64_4.6.0-1       MASS_7.3-65