MIFT Study 1 Analyses

Descriptive Statistics

stable:

Table continues below
	vars	n	mean	sd	median	trimmed
whitemulti_trust_dif	1	146	0.05325	0.5419	0.05	0.04216
White	2	146	3.141	0.5473	3.112	3.138
Multiracial	3	146	3.087	0.5689	3.1	3.102
Black	4	146	3.15	0.6761	3.225	3.196
trust_survey	5	151	5.037	0.8716	5.2	5.065
trust_therm	6	151	73.28	20.06	76	74.5
atma	7	151	3.612	0.5222	3.565	3.593
feel_therm	8	151	76.76	19.17	80	78.14
authen	9	151	5.583	0.9797	5.75	5.634
race_ess	10	151	3.769	1.243	4	3.848
pol_or	11	151	2.98	1.749	3	2.81

Table continues below
	mad	min	max	range	skew
whitemulti_trust_dif	0.3336	-1.625	2.075	3.7	0.5116
White	0.4633	1.825	4.8	2.975	0.07697
Multiracial	0.5189	1.6	4.625	3.025	-0.1833
Black	0.5745	1.025	4.825	3.8	-0.6243
trust_survey	0.8896	2.1	7	4.9	-0.4747
trust_therm	20.76	0	100	100	-0.6336
atma	0.5157	1.913	5	3.087	0.2233
feel_therm	22.24	0	100	100	-0.7478
authen	1.112	2.25	7	4.75	-0.511
race_ess	0.9266	1	6.75	5.75	-0.5577
pol_or	1.483	1	7	6	0.5573

	kurtosis	se
whitemulti_trust_dif	2.798	0.04485
White	0.2952	0.04529
Multiracial	0.2146	0.04708
Black	0.7151	0.05595
trust_survey	0.1179	0.07093
trust_therm	-0.03012	1.632
atma	0.2634	0.0425
feel_therm	0.3403	1.56
authen	-0.03323	0.07973
race_ess	-0.1913	0.1011
pol_or	-0.7237	0.1423

fluid:

Table continues below
	vars	n	mean	sd	median	trimmed
whitemulti_trust_dif	1	154	0.1278	0.4958	0.05	0.1063
White	2	154	3.064	0.4963	3.05	3.068
Multiracial	3	154	2.936	0.478	3	2.954
Black	4	154	3.049	0.574	3.075	3.07
trust_survey	5	155	5.018	0.812	5.1	5.027
trust_therm	6	155	71.58	18.59	75	71.42
atma	7	155	3.501	0.5045	3.478	3.494
feel_therm	8	155	74.77	18.47	78	75.08
authen	9	155	5.427	0.9816	5.5	5.458
race_ess	10	155	3.785	1.221	4	3.852
pol_or	11	155	2.832	1.662	3	2.664

Table continues below
	mad	min	max	range	skew	kurtosis
whitemulti_trust_dif	0.3706	-1.85	2.05	3.9	0.3656	2.715
White	0.4077	1.1	4.35	3.25	-0.2923	1.284
Multiracial	0.3892	1.2	4	2.8	-0.4798	0.9474
Black	0.5004	1.325	4.7	3.375	-0.4137	0.3793
trust_survey	0.7413	1.5	7	5.5	-0.5865	1.207
trust_therm	25.2	23	100	77	-0.1419	-1.028
atma	0.5157	2.174	4.783	2.609	0.0696	-0.1526
feel_therm	23.72	26	100	74	-0.2102	-1.151
authen	1.112	2.5	7	4.5	-0.4217	-0.1535
race_ess	1.112	1	6.875	5.875	-0.4488	-0.2572
pol_or	1.483	1	7	6	0.5264	-0.7724

	se
whitemulti_trust_dif	0.03996
White	0.03999
Multiracial	0.03852
Black	0.04625
trust_survey	0.06522
trust_therm	1.493
atma	0.04052
feel_therm	1.483
authen	0.07884
race_ess	0.0981
pol_or	0.1335

GEE Model for Speeded Trust Task

From preregistration:

For the speeded trust task, we will fit a GEE regression model with trustworthiness ratings for each target face as the outcome and target race (within subjects—will be dummy coded with White as the comparison group), condition (between subjects), and their interactions as predictors.

Findings:

The comparison group is White faces in the stable condition. The intercept is 3.1 on a scale from 1 to 5 (3 midpoint) with a higher score indicating greater trust.
Main effects
- There is a main effect of condition such that participants in the fluid condition report slightly less trust overall than participants in the stable condition.
- There is also a main effect of the Multiracial dummy code such that participants in both conditions report slightly less trust for Multiracial faces relative to White faces.
- There is also a main effect of the Black dummy code such that participants in both conditions report slightly less trust for Black faces relative to White faces.
All of these main effects are qualified by significant interactions.
- There is an interaction between condition and the Multiracial dummy code such that participants show lower trust for multiracial people in the fluid condition relative to the stable condition. There is no significant difference between conditions when faces are not multiracial.
- There is an interaction between condition and the Black dummy code such that people in the fluid condition show less trust for faces that are not Black than participants in the stable condition. There is no significant difference between conditions when faces are Black. This one doesn’t really make much sense to me and I think it may be driven by multiracial faces, especially as the means really aren’t that difference compared to the Black faces.

##           (Intercept)            condition1            race_multi 
##            3.10326101           -0.03913764           -0.09031568 
##            race_black condition1:race_multi condition1:race_black 
##           -0.00340361           -0.03744406           -0.01201847

Estimates for the speeded trust model
term	estimate	std.error	statistic	p.value	NA
(Intercept)	3.1033	0.0100	310.8978	0.0299	103.8124
condition1	-0.0391	0.0100	-3.9210	0.0299	-1.3093
race_multi	-0.0903	0.0141	-6.3980	0.0297	-3.0382
race_black	-0.0034	0.0141	-0.2411	0.0451	-0.0754
condition1:race_multi	-0.0374	0.0141	-2.6526	0.0297	-1.2596
condition1:race_black	-0.0120	0.0141	-0.8514	0.0451	-0.2663

Emmeans for condition * race_multi
condition	race_multi	emmean	SE	df	asymp.LCL	asymp.UCL
stable	0	3.1467	0.0366	Inf	3.0750	3.2184
fluid	0	3.0564	0.0314	Inf	2.9948	3.1180
stable	1	3.0938	0.0631	Inf	2.9702	3.2175
fluid	1	2.9287	0.0534	Inf	2.8241	3.0332

Post hoc tests for condition * race_multi
contrast	race_multi	estimate	SE	df	z.ratio	p.value
fluid - stable	0	-0.0903	0.0482	Inf	-1.8719	0.0612
fluid - stable	1	-0.1652	0.0826	Inf	-1.9994	0.0456

Emmeans for condition * race_black
condition	race_black	emmean	SE	df	asymp.LCL	asymp.UCL
stable	0	3.1160	0.0397	Inf	3.0381	3.1938
fluid	0	3.0002	0.0337	Inf	2.9342	3.0663
stable	1	3.1246	0.0714	Inf	2.9846	3.2645
fluid	1	2.9848	0.0604	Inf	2.8665	3.1032

Post hoc tests for condition * race_black
contrast	race_black	estimate	SE	df	z.ratio	p.value
fluid - stable	0	-0.1157	0.0521	Inf	-2.2215	0.0263
fluid - stable	1	-0.1398	0.0935	Inf	-1.4945	0.1351

T-tests for main dependent variables for differences between conditions

From preregistration:

For each of the five other dependent variables (listed below), we will run independent samples T-tests to determine if there is any difference between participants who read the fluidity article and participants who read the stability article.

Trust Survey

Findings:

There is not a significant difference in explicit trust on the trust survey between conditions.

Trust survey by condition (continued below)
Test statistic	df	P value	Alternative hypothesis
0.1974	301.2	0.8436	two.sided

mean in group stable	mean in group fluid
5.037	5.018

Trust Thermometer

Findings:

There is not a significant difference in explicit trust on the trust thermometer between conditions.

Trust thermometer by condition (continued below)
Test statistic	df	P value	Alternative hypothesis
0.7674	300.9	0.4434	two.sided

mean in group stable	mean in group fluid
73.28	71.58

Attitudes towards multiracial adults

Findings:

There is not a significant difference in attitudes towards multiracial adults between conditions. Though it is worth noting that there is a marginal difference in line with our hypothesis (more negative attitudes in stable condition).

Attitudes towards multiracial adults by condition (continued below)
Test statistic	df	P value	Alternative hypothesis
1.879	302.9	0.06126	two.sided

mean in group stable	mean in group fluid
3.612	3.501

Feeling thermometer

Findings:

There is not a significant difference in feelings towards multiracial people on the feeling thermometer between conditions.

Feeling thermometer by condition (continued below)
Test statistic	df	P value	Alternative hypothesis
0.9231	302.8	0.3567	two.sided

mean in group stable	mean in group fluid
76.76	74.77

Authenticity

Findings:

There is not a significant difference in perceived authenticity of multiracial people between conditions.

Authenticity by condition (continued below)
Test statistic	df	P value	Alternative hypothesis
1.386	303.8	0.1669	two.sided

mean in group stable	mean in group fluid
5.583	5.427

Exploratory Analyses.

From Preregistration:

“We will run an exploratory independent samples T-test to determine if there is any difference in race essentialism between participants who read the fluidity article and participants who read the stability article. If we find that there are no differences in race essentialism between conditions, we will examine whether race essentialism moderates the relationship between which article participants read and each of the six dependent variables.”

Race Essentialism

T-test

Findings:

There is not a significant difference in race essentialism between conditions Thus, we will move forward to examine whether race essentialism moderates the relationship between condition and the dependent variables.

Race essentialism by condition (continued below)
Test statistic	df	P value	Alternative hypothesis
-0.111	303.4	0.9117	two.sided

mean in group stable	mean in group fluid
3.769	3.785

Speeded trust task by condition + race essentialism as moderator

From preregistration:

“For the speeded trust task, we will first calculate a White/Multiracial trust difference score by subtracting participant’s average trust ratings for all multiracial targets from participant’s average trust ratings for all White targets, with a higher number indicating greater trust towards White targets relative to multiracial targets. We then will fit a linear regression model with the White/Multiracial trust difference score as the outcome and condition, race essentialism, and the interaction term between the two as predictors. If we find that the interactions is significant, we will conduct simple slopes analysis to probe the interaction.”

Findings:

Main Effects
- There is no main effect of condition. Confused by this as there is when analyzed with the GEE.
- There is a main effect of race essentialism such that participants who are more essentialist about race show greater trust towards White targets relative to Multiracial targets.
Interaction
- There is no significant interaction. In other words, race essentialism does not moderate the relationship between condition and trust.

Estimates for the speeded trust model
term	estimate	std.error	statistic	p.value
(Intercept)	-0.2206	0.0947	-2.3306	0.0204
condition1	0.0685	0.0947	0.7242	0.4695
race_ess	0.0827	0.0239	3.4603	0.0006
condition1:race_ess	-0.0087	0.0239	-0.3633	0.7166

Summary for the speeded trust model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0442	0.0345	0.5102	4.5639	0.0038	3	-221.784	453.567	472.086	77.0506	296	300

Other main DVs by condition + race essentialism as moderator

From preregistration:

“For each of the five other dependent variables, we will fit an individual linear regression model including condition, race essentialism, and the interaction term between the two as predictors. If we find a significant interaction between condition and race essentialism for any of the models, we will conduct simple slopes analysis for that model to probe the interaction.”

Trust survey

Findings:

Main Effects
- There is no main effect of condition.
- There is a main effect of race essentialism such that participants who are more essentialist about race show less trust towards multiracial people.
Interaction
- There is no significant interaction. In other words, race essentialism does not moderate the relationship between condition and trust.

Estimates for the trust survey model
term	estimate	std.error	statistic	p.value
(Intercept)	5.4446	0.1536	35.4380	0.0000
condition1	0.2001	0.1536	1.3027	0.1937
race_ess	-0.1103	0.0387	-2.8512	0.0047
condition1:race_ess	-0.0553	0.0387	-1.4291	0.1540

Summary for the trust survey model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0326	0.023	0.8309	3.3925	0.0183	3	-375.499	760.999	779.617	208.503	302	306

Trust Thermometer

Findings:

Main Effects
- There is no main effect of condition.
- There is a main effect of race essentialism such that participants who are more essentialist about race show less trust towards multiracial people.
Interaction
- There is no significant interaction. In other words, race essentialism does not moderate the relationship between condition and trust.

Estimates for the trust thermometer model
term	estimate	std.error	statistic	p.value
(Intercept)	79.6541	3.5516	22.4277	0.0000
condition1	2.8688	3.5516	0.8078	0.4199
race_ess	-1.9109	0.8943	-2.1368	0.0334
condition1:race_ess	-0.9803	0.8943	-1.0963	0.2738

Summary for the trust thermometer model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0206	0.0108	19.2079	2.1151	0.0983	3	-1336.51	2683.02	2701.64	111421	302	306

Attitudes towards multiracial adults

Findings:

Main Effects
- There is no main effect of condition.
- There is no main effect of race essentialism. It is worth noting that this is marginal such that participants who are more essentialist about race show more negative attitudes towards multiracial people.
Interaction
- There is no significant interaction. In other words, race essentialism does not moderate the relationship between condition and attitudes towards multiracial adults.

Estimates for the attitudes towards multiracial adults model
term	estimate	std.error	statistic	p.value
(Intercept)	3.7325	0.0946	39.4506	0.0000
condition1	-0.0248	0.0946	-0.2622	0.7933
race_ess	-0.0466	0.0238	-1.9567	0.0513
condition1:race_ess	-0.0079	0.0238	-0.3332	0.7392

Summary for the attitudes towards multiracial adults model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0242	0.0145	0.5117	2.4964	0.0599	3	-227.151	464.303	482.92	79.0719	302	306

Feeling thermometer

Findings:

Main Effects
- There is no main effect of condition.
- There is no main effect of race essentialism. Though again perhaps can be considered marginal such that participants who are more essentialist about race show more negative attitudes towards multiracial people.
Interaction
- There is no significant interaction. In other words, race essentialism does not moderate the relationship between condition and attitudes.

Estimates for the feeling thermometer model
term	estimate	std.error	statistic	p.value
(Intercept)	81.6797	3.4611	23.5993	0.0000
condition1	3.7944	3.4611	1.0963	0.2738
race_ess	-1.5627	0.8715	-1.7931	0.0740
condition1:race_ess	-1.2645	0.8715	-1.4510	0.1478

Summary for the feeling thermometer model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.02	0.0103	18.7185	2.0536	0.1064	3	-1328.61	2667.23	2685.84	105816	302	306

Authenticity

Findings:

Main Effects
- There is no main effect of condition.
- There is a main effect of race essentialism such that participants who are more essentialist about race perceive multiracial people as less authentic.
Interaction
- There is no significant interaction. In other words, race essentialism does not moderate the relationship between condition and authenticity.

Estimates for the authenticity model
term	estimate	std.error	statistic	p.value
(Intercept)	6.2849	0.1755	35.8046	0.0000
condition1	0.0525	0.1755	0.2994	0.7649
race_ess	-0.2064	0.0442	-4.6700	0.0000
condition1:race_ess	-0.0341	0.0442	-0.7705	0.4416

Summary for the authenticity model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0748	0.0656	0.9493	8.1404	0	3	-416.272	842.543	861.161	272.173	302	306

Race & political orientation

From preregistration:

Additionally, we will conduct exploratory analyses to examine whether participants’ responses vary by participant race and political orientation..

Personally I would not read into the participant race effects too much due to the small Ns in some cells.

Participant Race
White	Black	Latine	Asian	Other
232	32	16	18	7

Speeded trust task by condition + participant race and political orientation as moderators

From preregistration:

For the speeded trust task, we will again use the White/Multiracial trust difference score as described above. We then will fit a linear regression model with the White/Multiracial trust difference score as the outcome and condition, participant race, political orientation, and the two two-way interaction terms between condition, and participant race/political orientation (i.e., condition X participant race, condition X political orientation) as predictors. If we find that any of the interactions are significant, we will conduct simple slopes analysis to probe the interaction.

Findings:

Main Effects
- There is no main effect of condition
- There are no main effects of participant race
- There is a main effect of political orientation such that participants that are more conservative show greater trust for white faces relative to multiracial faces.
Interactions
- There are no interactions between participant race and condition
- There is no interaction between condition and political orientation.

White, Black, Latine, Asian and Other

Estimates for the speeded trust model
term	estimate	std.error	statistic	p.value
(Intercept)	-0.1430	0.0784	-1.8250	0.0690
condition1	0.0773	0.0784	0.9870	0.3245
race_factor1	-0.0581	0.0477	-1.2164	0.2248
race_factor2	0.0310	0.0463	0.6702	0.5033
race_factor3	0.0303	0.0333	0.9096	0.3638
race_factor4	-0.0287	0.0437	-0.6549	0.5130
pol_or	0.0776	0.0174	4.4572	0.0000
condition1:race_factor1	0.0002	0.0477	0.0045	0.9964
condition1:race_factor2	0.0638	0.0463	1.3782	0.1692
condition1:race_factor3	-0.0467	0.0333	-1.4008	0.1624
condition1:race_factor4	-0.0292	0.0437	-0.6674	0.5050
condition1:pol_or	-0.0160	0.0174	-0.9203	0.3582

Summary for the speeded trust model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0932	0.0585	0.504	2.6823	0.0027	11	-213.268	452.537	500.642	72.9016	287	299

Other main DVs by condition + participant race and political orientation as moderators

From preregistration:

For each of the five other dependent variables, we will fit an individual linear regression model including condition, participant race, political orientation, and the two-way interaction terms between condition and each demographic variable (i.e., condition X participant race, condition X political orientation) as predictors. If we find a significant effect for either of the interaction terms for any of the models, we will conduct simple slopes analysis for that model to probe the interaction.

Trust survey

Findings:

Main Effects
- There is no main effect of condition
- There are no main effects of participant race aside from Black participants. Black participants show lower trust for multiracial people.
- There is a main effect of political orientation such that participants that are more conservative show lower trust for multiracial people.
Interactions
- There are no interactions between participant race and condition
- There is no interaction between condition and political orientation

White, Black, Latine, Asian and Other

Estimates for the trust survey model
term	estimate	std.error	statistic	p.value
(Intercept)	5.1332	0.1270	40.4117	0.0000
condition1	-0.0243	0.1270	-0.1914	0.8484
race_factor1	-0.1721	0.0777	-2.2151	0.0275
race_factor2	-0.0324	0.0755	-0.4286	0.6686
race_factor3	-0.0821	0.0543	-1.5104	0.1320
race_factor4	0.0447	0.0713	0.6273	0.5310
pol_or	-0.0920	0.0280	-3.2858	0.0011
condition1:race_factor1	-0.1258	0.0777	-1.6185	0.1066
condition1:race_factor2	0.0092	0.0755	0.1219	0.9030
condition1:race_factor3	0.0905	0.0543	1.6649	0.0970
condition1:race_factor4	0.0122	0.0713	0.1718	0.8637
condition1:pol_or	0.0055	0.0280	0.1967	0.8442

Summary for the trust survey model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0822	0.0477	0.8216	2.3858	0.0077	11	-366.733	759.466	807.83	197.797	293	305

Trust Thermometer

Findings:

Main Effects
- There is no main effect of condition
- There are no main effects of participant race aside from Asian participants. Asian participants show lower trust for multiracial people.
- There is a main effect of political orientation such that participants that are more conservative show less trust for multiracial people.
Interactions
- There are no interactions between participant race and condition aside from asian participants who showed lower trust than White participants for multiracial people only in the stable condition.
- There is no interaction between condition and political orientation

White, Black, Latine, Asian and Other

Estimates for the trust thermometer model
term	estimate	std.error	statistic	p.value
(Intercept)	74.2402	2.9416	25.2379	0.0000
condition1	0.4594	2.9416	0.1562	0.8760
race_factor1	-1.0616	1.7996	-0.5899	0.5557
race_factor2	-0.2552	1.7482	-0.1460	0.8840
race_factor3	-2.9791	1.2583	-2.3675	0.0186
race_factor4	0.3931	1.6506	0.2381	0.8120
pol_or	-1.6707	0.6482	-2.5776	0.0104
condition1:race_factor1	-1.4529	1.7996	-0.8073	0.4201
condition1:race_factor2	-0.6656	1.7482	-0.3807	0.7037
condition1:race_factor3	2.6777	1.2583	2.1280	0.0342
condition1:race_factor4	1.1631	1.6506	0.7046	0.4816
condition1:pol_or	0.0695	0.6482	0.1072	0.9147

Summary for the trust thermometer model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0612	0.026	19.0276	1.7373	0.0649	11	-1325.15	2676.3	2724.67	106080	293	305

Emmeans for condition * race_asian
condition	race_factor	emmean	SE	df	lower.CL	upper.CL
stable	White	74.3566	1.7637	293	70.8855	77.8278
fluid	White	72.2338	1.7764	293	68.7376	75.7300
stable	Black	75.1391	4.9130	293	65.4699	84.8084
fluid	Black	67.2048	4.6219	293	58.1084	76.3012
stable	Latine	75.9790	6.0503	293	64.0714	87.8867
fluid	Latine	66.9571	7.7710	293	51.6629	82.2512
stable	Asian	52.5311	7.1937	293	38.3732	66.6891
fluid	Asian	67.5931	5.7588	293	56.2592	78.9269
stable	Other	65.6515	13.5874	293	38.9101	92.3928
fluid	Other	76.2777	8.5139	293	59.5216	93.0339

Post hoc tests for condition * race_asian
contrast	condition	estimate	SE	df	t.ratio	p.value
Black - White	stable	0.7825	5.2208	293	0.1499	0.9999
Latine - White	stable	1.6224	6.3150	293	0.2569	0.9990
Latine - Black	stable	0.8399	7.7913	293	0.1078	1.0000
Asian - White	stable	-21.8255	7.4097	293	-2.9455	0.0285
Asian - Black	stable	-22.6080	8.7107	293	-2.5954	0.0738
Asian - Latine	stable	-23.4479	9.3884	293	-2.4975	0.0940
Other - White	stable	-8.7052	13.6838	293	-0.6362	0.9691
Other - Black	stable	-9.4877	14.4525	293	-0.6565	0.9653
Other - Latine	stable	-10.3276	14.9542	293	-0.6906	0.9584
Other - Asian	stable	13.1203	15.3951	293	0.8522	0.9138
Black - White	fluid	-5.0290	4.9560	293	-1.0147	0.8485
Latine - White	fluid	-5.2767	7.9691	293	-0.6621	0.9642
Latine - Black	fluid	-0.2477	9.0478	293	-0.0274	1.0000
Asian - White	fluid	-4.6407	6.0194	293	-0.7710	0.9388
Asian - Black	fluid	0.3883	7.4014	293	0.0525	1.0000
Asian - Latine	fluid	0.6360	9.6610	293	0.0658	1.0000
Other - White	fluid	4.0440	8.7000	293	0.4648	0.9904
Other - Black	fluid	9.0730	9.6802	293	0.9373	0.8822
Other - Latine	fluid	9.3207	11.5324	293	0.8082	0.9280
Other - Asian	fluid	8.6847	10.2921	293	0.8438	0.9167

Attitudes towards multiracial adults

Findings:

Main Effects
- There is no main effect of condition
- There are no main effects of participant race aside from Black participants. Black participants show more negative attitudes towards multiracial people than White participants.
- There is no main effect of political orientation.
Interactions
- There are no interactions between participant race and condition aside from asian participants but when I probed this literally nothing was significant.
- There is no interaction between condition and political orientation

White, Black, Latine, Asian and Other

Estimates for the attitudes towards multiracial adults model
term	estimate	std.error	statistic	p.value
(Intercept)	3.4602	0.0784	44.1449	0.0000
condition1	-0.0220	0.0784	-0.2801	0.7796
race_factor1	-0.1103	0.0480	-2.3007	0.0221
race_factor2	-0.0529	0.0466	-1.1360	0.2569
race_factor3	-0.0139	0.0335	-0.4131	0.6799
race_factor4	-0.0176	0.0440	-0.4005	0.6891
pol_or	-0.0164	0.0173	-0.9524	0.3417
condition1:race_factor1	-0.0217	0.0480	-0.4526	0.6512
condition1:race_factor2	-0.0562	0.0466	-1.2062	0.2287
condition1:race_factor3	0.0742	0.0335	2.2143	0.0276
condition1:race_factor4	0.0538	0.0440	1.2230	0.2223
condition1:pol_or	0.0055	0.0173	0.3165	0.7518

Summary for the attitudes towards multiracial adults model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0664	0.0313	0.507	1.893	0.0399	11	-219.494	464.989	513.353	75.3197	293	305

Feeling thermometer

Findings:

Main Effects
- There is no main effect of condition
- There are no main effects of participant race aside from Asian participants. Asian participants show more negative attitudes towards multiracial people than White participants.
- There is a main effect of political orientation such that participants that are more conservative show more negative feelings towards multiracial people.
Interactions
- There are no interactions between participant race and condition.
- There is no interaction between condition and political orientation

White, Black, Latine, Asian and Other

Estimates for the feeling thermometer model
term	estimate	std.error	statistic	p.value
(Intercept)	79.0028	2.8549	27.6727	0.0000
condition1	-0.3247	2.8549	-0.1137	0.9095
race_factor1	-1.7866	1.7466	-1.0229	0.3072
race_factor2	0.4398	1.6967	0.2592	0.7956
race_factor3	-2.7363	1.2212	-2.2406	0.0258
race_factor4	0.2800	1.6020	0.1748	0.8614
pol_or	-2.0408	0.6291	-3.2443	0.0013
condition1:race_factor1	-0.7898	1.7466	-0.4522	0.6515
condition1:race_factor2	-1.0373	1.6967	-0.6114	0.5414
condition1:race_factor3	2.0191	1.2212	1.6533	0.0993
condition1:race_factor4	0.7897	1.6020	0.4930	0.6224
condition1:pol_or	0.1168	0.6291	0.1858	0.8528

Summary for the feeling thermometer model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.0684	0.0334	18.4667	1.9562	0.0325	11	-1316.03	2658.05	2706.41	99918.4	293	305

Authenticity

Findings:

Main Effects
- There is no main effect of condition
- There are no main effects of participant race aside from Black participants. Black participants perceive multiracial people as less authentic than White participants.
- There is a main effect of political orientation such that participants that are more conservative perceive multiracial people as less authentic.
Interactions
- There are no interactions between participant race and condition.
- There is no interaction between condition and political orientation

White, Black, Latine, Asian and Other

Estimates for the authenticity model
term	estimate	std.error	statistic	p.value
(Intercept)	5.7121	0.1443	39.5772	0.0000
condition1	-0.1069	0.1443	-0.7407	0.4595
race_factor1	-0.2993	0.0883	-3.3892	0.0008
race_factor2	0.0247	0.0858	0.2879	0.7736
race_factor3	-0.0586	0.0617	-0.9484	0.3437
race_factor4	0.0384	0.0810	0.4741	0.6358
pol_or	-0.1398	0.0318	-4.3975	0.0000
condition1:race_factor1	-0.0511	0.0883	-0.5784	0.5635
condition1:race_factor2	-0.0794	0.0858	-0.9263	0.3551
condition1:race_factor3	0.0457	0.0617	0.7404	0.4597
condition1:race_factor4	0.1068	0.0810	1.3188	0.1883
condition1:pol_or	0.0192	0.0318	0.6045	0.5460

Summary for the authenticity model
r.squared	adj.r.squared	sigma	statistic	p.value	df	logLik	AIC	BIC	deviance	df.residual	nobs
0.1253	0.0924	0.9336	3.8145	0	11	-405.691	837.381	885.745	255.367	293	305

Additional Exploratory Descriptives looking at main Dvs by participant race

White:

Table continues below
	vars	n	mean	sd	median	trimmed
whitemulti_trust_dif	1	226	0.1077	0.5365	0.075	0.0886
White	2	226	3.148	0.5205	3.125	3.148
Multiracial	3	226	3.04	0.5316	3.037	3.045
Black	4	226	3.135	0.6417	3.2	3.169
trust_survey	5	232	5.105	0.8172	5.2	5.121
trust_therm	6	232	73.25	18.95	76	73.77
atma	7	232	3.607	0.5245	3.609	3.598
feel_therm	8	232	76.83	18.38	80	77.86
authen	9	232	5.596	0.953	5.75	5.644
race_ess	10	232	3.741	1.281	4	3.823
pol_or	11	232	2.927	1.728	3	2.763

Table continues below
	mad	min	max	range	skew	kurtosis
whitemulti_trust_dif	0.3706	-1.85	2.075	3.925	0.4381	2.901
White	0.4077	1.1	4.8	3.7	-0.155	1.143
Multiracial	0.4448	1.2	4.625	3.425	-0.1496	0.5699
Black	0.5745	1.025	4.825	3.8	-0.5228	0.5749
trust_survey	0.7413	2.1	7	4.9	-0.4199	0.1667
trust_therm	21.5	0	100	100	-0.4864	-0.2401
atma	0.5157	1.913	5	3.087	0.01722	0.1945
feel_therm	20.76	0	100	100	-0.6292	0.08296
authen	1.112	2.75	7	4.25	-0.4604	-0.2884
race_ess	1.112	1	6.875	5.875	-0.5069	-0.2993
pol_or	1.483	1	7	6	0.5286	-0.8524

	se
whitemulti_trust_dif	0.03569
White	0.03462
Multiracial	0.03536
Black	0.04269
trust_survey	0.05365
trust_therm	1.244
atma	0.03444
feel_therm	1.206
authen	0.06257
race_ess	0.0841
pol_or	0.1134

Black:

Table continues below
	vars	n	mean	sd	median	trimmed
whitemulti_trust_dif	1	32	0.001562	0.3868	0	0.005769
White	2	32	2.998	0.4684	3	2.972
Multiracial	3	32	2.996	0.482	3	3.011
Black	4	32	3.166	0.4591	3.088	3.149
trust_survey	5	32	4.737	0.9431	5	4.823
trust_therm	6	32	70.72	20.76	73	71.27
atma	7	32	3.379	0.423	3.326	3.336
feel_therm	8	32	72.91	20.99	72.5	73.19
authen	9	32	4.977	1.082	5	5.058
race_ess	10	32	4.262	0.9144	4.375	4.303
pol_or	11	32	3.031	1.732	3	2.846

Table continues below
	mad	min	max	range	skew
whitemulti_trust_dif	0.2965	-0.9	1.05	1.95	0.1138
White	0.4262	2.025	4.4	2.375	0.6275
Multiracial	0.3521	1.55	4.2	2.65	-0.3706
Black	0.3706	2.2	4.375	2.175	0.5086
trust_survey	0.8154	1.5	6.2	4.7	-1.304
trust_therm	29.65	30	100	70	-0.2279
atma	0.419	2.826	4.304	1.478	0.7558
feel_therm	32.62	35	100	65	-0.03147
authen	0.7413	2.25	6.75	4.5	-0.6458
race_ess	0.556	2	6	4	-0.4361
pol_or	1.483	1	7	6	0.5673

	kurtosis	se
whitemulti_trust_dif	0.84	0.06837
White	0.9494	0.0828
Multiracial	1.783	0.08521
Black	0.1777	0.08116
trust_survey	2.369	0.1667
trust_therm	-1.184	3.67
atma	-0.4342	0.07478
feel_therm	-1.575	3.711
authen	0.2267	0.1913
race_ess	0.3281	0.1616
pol_or	-0.4265	0.3061

Latine:

Table continues below
	vars	n	mean	sd	median	trimmed
whitemulti_trust_dif	1	16	0.0375	0.6044	0	0.03036
White	2	16	2.83	0.5192	2.975	2.85
Multiracial	3	16	2.792	0.3637	2.775	2.796
Black	4	16	2.889	0.5585	3	2.943
trust_survey	5	16	4.912	0.7873	5.05	4.929
trust_therm	6	16	73.5	20.67	78	74.43
atma	7	16	3.41	0.5902	3.391	3.379
feel_therm	8	16	78.75	18.67	82.5	79.29
authen	9	16	5.547	1.022	5.625	5.571
race_ess	10	16	3.602	1.111	3.688	3.607
pol_or	11	16	2.375	1.544	2	2.214

Table continues below
	mad	min	max	range	skew
whitemulti_trust_dif	0.2595	-1.275	1.45	2.725	-0.02441
White	0.5004	1.825	3.55	1.725	-0.479
Multiracial	0.4262	2.1	3.425	1.325	-0.1171
Black	0.5004	1.375	3.65	2.275	-0.9438
trust_survey	1.112	3.6	6	2.4	-0.1166
trust_therm	25.95	34	100	66	-0.3034
atma	0.5479	2.435	4.826	2.391	0.4591
feel_therm	25.2	50	100	50	-0.3485
authen	0.7413	3.75	7	3.25	-0.2199
race_ess	0.834	1.5	5.625	4.125	0.0484
pol_or	1.483	1	6	5	0.7294

	kurtosis	se
whitemulti_trust_dif	0.7412	0.1511
White	-1.127	0.1298
Multiracial	-1.06	0.09094
Black	0.9455	0.1396
trust_survey	-1.425	0.1968
trust_therm	-1.298	5.167
atma	-0.04476	0.1475
feel_therm	-1.409	4.668
authen	-0.9538	0.2554
race_ess	-0.6152	0.2777
pol_or	-0.5891	0.386

Asian:

Table continues below
	vars	n	mean	sd	median	trimmed
whitemulti_trust_dif	1	18	0.1569	0.5015	0	0.1344
White	2	18	3.065	0.5423	2.95	3.062
Multiracial	3	18	2.908	0.6143	2.975	2.939
Black	4	18	2.785	0.6276	2.875	2.812
trust_survey	5	18	4.667	0.7639	4.6	4.706
trust_therm	6	18	62.39	18.42	63	62.31
atma	7	18	3.43	0.4358	3.457	3.416
feel_therm	8	18	66.56	18.37	67.5	66.56
authen	9	18	5.139	0.8054	5	5.141
race_ess	10	18	3.549	1.141	3.688	3.539
pol_or	11	18	2.5	1.425	2	2.438

Table continues below
	mad	min	max	range	skew
whitemulti_trust_dif	0.3892	-0.6	1.275	1.875	0.5292
White	0.4448	2.025	4.15	2.125	0.2427
Multiracial	0.7042	1.675	3.65	1.975	-0.5556
Black	0.6116	1.45	3.675	2.225	-0.6914
trust_survey	0.8896	3.1	5.6	2.5	-0.1829
trust_therm	19.27	26	100	74	0.09683
atma	0.3545	2.696	4.391	1.696	0.3104
feel_therm	22.98	33	100	67	-0.02402
authen	0.7413	3.75	6.5	2.75	0.06121
race_ess	1.297	1.625	5.625	4	-0.04313
pol_or	1.483	1	5	4	0.4035

	kurtosis	se
whitemulti_trust_dif	-0.6405	0.1182
White	-0.7601	0.1278
Multiracial	-1.018	0.1448
Black	-0.3524	0.1479
trust_survey	-1.26	0.1801
trust_therm	-0.5888	4.341
atma	-0.436	0.1027
feel_therm	-1.157	4.33
authen	-1.187	0.1898
race_ess	-1.296	0.2689
pol_or	-1.326	0.3358

Other:

Table continues below
	vars	n	mean	sd
whitemulti_trust_dif	1	7	-0.00000000000000008128	0.3503
White	2	7	2.807	0.587
Multiracial	3	7	2.807	0.6932
Black	4	7	2.825	0.7388
trust_survey	5	7	4.986	1.139
trust_therm	6	7	71.86	20.13
atma	7	7	3.416	0.3558
feel_therm	8	7	73.86	20.06
authen	9	7	5.5	0.9895
race_ess	10	7	3.714	1.038
pol_or	11	7	3.714	1.799

Table continues below
	median	trimmed	mad	min
whitemulti_trust_dif	0.05	-0.0000000000000000793	0.4077	-0.625
White	2.675	2.807	0.2224	1.95
Multiracial	3.075	2.807	0.6301	1.6
Black	3.15	2.825	0.7784	1.85
trust_survey	5	4.986	1.483	3.3
trust_therm	72	71.86	19.27	39
atma	3.478	3.416	0.3223	2.739
feel_therm	80	73.86	22.24	45
authen	5.75	5.5	0.3706	4
race_ess	3.75	3.714	0.3706	1.75
pol_or	4	3.714	1.483	1

	max	range	skew	kurtosis	se
whitemulti_trust_dif	0.35	0.975	-0.6325	-1.222	0.1324
White	3.6	1.65	0.1705	-1.497	0.2219
Multiracial	3.5	1.9	-0.549	-1.366	0.262
Black	3.675	1.825	-0.3027	-1.836	0.2792
trust_survey	6.4	3.1	-0.06522	-1.641	0.4306
trust_therm	100	61	-0.2121	-1.361	7.608
atma	3.826	1.087	-0.7171	-0.8049	0.1345
feel_therm	100	55	-0.196	-1.748	7.583
authen	7	3	-0.1244	-1.332	0.374
race_ess	5.125	3.375	-0.5728	-0.6523	0.3922
pol_or	7	6	0.3633	-0.6652	0.6801