@silentchief said:
Bahaha. Do you honestly think anyone should take this trash seriously?
Most of Americans? (60%)
‘A country on fire’: New poll finds America polarized over culture, race and ‘woke’ (yahoo.com)
@silentchiefsaid:
Lol keep posting it it won't change the fact they are trash studies.
Garbage opinion. Provide counter studies.
You have to actually refute them all of my 13 studies with data through citation. I'll give you a few specific examples of what you need to refute for some of them or show a study that simply has conflicting data:
One,
Table 2provides odds ratios (OR), 95% confidence intervals, and significance thresholds from multilevel binary logit estimates. ORs greater than one represent a positive association, while ORs less than one represent a negative association with each behavioral outcome. For example, between 2013 and 2021, the odds of victims exhibiting signs of mental illness during encounters havedeclinedby around 10% each year (OR = .908; p< .001). Conversely, odds of victims being armed (OR = 1.070) or fleeing the scene (OR = 1.116) haveincreasedeach year (p< .001). The age of the victim is also a significant predictor of each outcome (p< .001). Older age predicts greater odds of exhibiting mental illness (OR = 1.017) and being armed at the scene (OR = 1.014), but lower odds of fleeing the scene (OR = .966). Relative to female victims, male victims also have significantly greater odds of being armed (OR = 1.699; p< .001) and fleeing the scene (OR = 1.418; p< .05).
The bottom of Table 2 displays coefficients by race. Relative to their White peers, Black victims have 60% lower odds of exhibiting mental illness (OR = .402; p < .001), 17% lower odds of being armed at the scene (OR = .826; p < .01), but 28% greater odds of fleeing the scene (OR = 1.279; p < .01). Hispanic victims also have 45% lower odds of exhibiting mental illness relative to Whites (OR = .545; p < .001), but otherwise are comparable. When comparing Hispanic and Black victims, Hispanic victims have 35% greater odds of exhibiting mental illness (p < .01), 18% lower odds of fleeing the scene (p < .05), but similar odds of being armed (not shown). These racial patterns hold regardless of the year of the encounter, age of victim, gender of victim, and the geographical clustering of encounters.Figures 1 through 3 plot racial differences in behaviors as average marginal probabilities, with covariates held at their respective means. Figure 1 shows that White victims have a 32% predicted probability of exhibiting mental illness, while Black and Hispanic victims have respective probabilities of 16% and 21%. In Figure 2, White victims have an 80% predicted probability of being armed, while Black and Hispanic victims have respective probabilities of 77% and 78%. Finally, Figure 3 shows that Black victims have the highest average probability of fleeing the scene at 33%, followed by Hispanic (29%) and White (28%) victims.
In a nationwide database of police killings between 2013 and 2021, I found that Black victims of police killings were overrepresented, and their White peers underrepresented, relative to the general US population. I also found that Black victims were less likely than their White peers to exhibit signs of mental illness or be armed at the scene of their killings, and more likely to flee the scene. Hispanics were less likely than Whites to exhibit signs of mental illness, but no more or less likely to be armed or flee. All the above patterns persisted even after accounting for heterogeneity by state, zip code, and neighborhood type in which fatal encounters occurred.This study provides rigorous and compelling evidence of systemic racism in police killings across the United States. Data for this study encompassed all 50 states and the Washington, D.C. area; over 4,000 five-digit zip codes; and a mix of suburban, urban, and rural neighborhoods. Despite such geographic heterogeneity, White victims appeared to pose greater threats to the safety of police officers than Black or Hispanic victims, yet also were underrepresented in police killings relative to the general US population.
Put another way, the threshold for being perceived as dangerous, and thereby falling victim to lethal police force, appears to be higher for White civilians relative to their Black or Hispanic peers. These findings are consistent with the notion of systemic pro-White/anti-Black racism in policing nationwide.This study has broader implications for policing, policymaking, and public health. First, current findings are supportive of campaigns to diversify and retrain police officers in efforts to curb racial disparities in the use of lethal police force. For example, other studies have found that Black and Hispanic officers tend to use less force and make fewer stops or arrests, relative to their White peers, especially in majority-Black or Hispanic neighborhoods (Ba et al., 2021; Legewie & Fagan, 2016). The present study suggests that Black and Hispanic officers may be more understanding of the skepticism and fear that POC civilians express toward police officers, given the racist legacies of policing in our country (Alexander, 2010; Gruber, 2021). Thus, police officers—especially White officers—should be better trained on how to anticipate and manage, without lethal force, Black and Hispanic civilians who express hostility or trepidation toward them.
Two,
The relationship between U.S. House of Representatives districts and state House of Representatives districts varies widely across the nation and within individual states.1 In Iowa, every state House district is entirely nested within one U.S. House district, meaning there are no unnecessary overlaps between districts at the state and federal levels. In the districts in place from 2012 to 2022 in South Carolina, by contrast, U.S. House districts unnecessarily overlap with a number that varies between 1 and 17 state House districts.2
Congressional districts that coincide with state legislative districts make it easier for voters to cast informed ballots, facilitate political mobilization and coordination among parties and candidates, and encourage cooperation among officeholders (e.g., Bibby and Maisel 2002; Carson et al. 2011, 2012). Conversely, voters in congressional districts that unnecessarily overlap with many state House districts share the same federal and state representation with fewer of their neighbors, a circumstance associated with less responsive government performance (Bowen 2014; Stashko 2020).
Here, we proffer the unnecessary overlap of congressional and state House districts as an indicator of gerrymandering and measure whether such overlaps are imposed in a racially disparate fashion. We find, in both bivariate and multivariate analysis, that race strongly affects the imposition of unnecessary overlaps. This suggests the drawing of incongruent district boundaries may represent a racially disparate burden on representation imposed by mapmakers.
Three,
Figure 2.
In 2019, racial disparities in funding rates corresponded to hundreds of awards in surplus to white PIs and hundreds of awards in deficit to other groups. Each box represents 10 proposals. Light gray boxes are unsuccessful proposals; colored boxes are funded proposals (awards). The black outlines represent 27.4% of the proposals submitted by each group, where 27.4% is the overall funding rate in 2019. For each group, the number of awards above (surplus) or below (deficit) this threshold is in bold. This graphic does not include proposals by multiracial PIs or PIs who did not provide their race or ethnicity.Source data: Data S1 in the accompanying data repository (https://doi.org/10.5061/dryad.2fqz612rt).The relative contributions of proposals by PIs from each group remain unchanged despite shifts in the number of pro-posals submitted by each group over time. Submissions by white PIs comprise the majority of proposals throughout the study period (Figure 1–figure supplement 2). In 2019, the competitive pool of proposals included 20,400 submissions by white PIs (66% among proposals from PIs who identified their race); 9,241 by Asian PIs (29%); 1,549 by Hispanic or Latino PIs (5%); 929 by Black/AA PIs (3%); 99 by AI/AN PIs (0.3%); and 47 by NH/PI PIs (0.2%) (Figure 2). Groups with fewer proposals experiencedthe greatest year-to-year variability in relative funding rates.These persistent funding rate disparities are realized as large differences in the absolute number of proposals awarded to PIs in each group. For example, of the 41,024 proposals considered in 2019, the NSF selected 11,243 for funding, or 27.4%. Proposals by white PIs were funded above this overall rate at 31.3%, yielding 6,389 awards (Figure 2). If pro-posals by white PIs had been funded instead at the overall rate of 27.4%, only 5,591 proposals would have been awarded. Thus, an “award surplus” of 798 awards was made to white PIs above the overall funding rate in 2019. In contrast, proposals submitted by the next largest racial group, Asian PIs, were funded at a 22.7% rate, yielding 2,073 awards. If the funding rate for proposals by Asian PIs had been equal to the overall rate, one would instead expect Chen CY, Kahanamoku SS, Tripati A, Alegado RA, Morris VR, Andrade K, Hosbey J(2022)eLife.11:e83071. doi: https://doi.org/10.7554/eLife.8307152,505 awards, or 432 additional awards. We refer to the number of awards required to bridge such gaps in funding rate as the “award deficit
I can do this for each but it's getting too spammy.
You're deliberately ignoring the data sets which need to be proven incorrect. They are drawing their conclusions directly from the results.
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