Children can pick up these implicit cues.”
Inference Indicator: (implicit: (...therefore...)
The data comes from 10 years of responses to an implicit association test.
"Because people have limited control and awareness of implicit bias, then people should be less defensive," Onyeador said.
“Implicit bias” is a term of art, used in a variety of ways.
So we require an account of what an “implicit” convention amounts to.
First, are agents morally responsible for their implicit biases (§4.1)?
Arguably the most common understanding is that “implicit” means “unconscious.”
One might for instance try to look for implicit hierarchies rather than explicit hierarchies.
One sort of skeptical worry stems from research on the effects of implicit bias on perception (§3.2.1).
It is, however, unclear who, if anyone, thinks that implicit bias is more important than explicit bias.
In examples 2 and 3, arguments depend on implicit claims which need to be considered when assessing the arguments.
But if people are aware of their implicit biases, then implicit measures are most likely not assessing unconscious “dual” attitudes.
"One of the reasons people use the implicit-bias framing is that it makes participants, white participants in particular, less defensive," Onyeador explained.
The fact that implicit biases seem to “rebound” in response to intentional efforts to suppress them supports this interpretation (Huebner 2009; Follenfant & Ric 2010).
Research on implicit bias has received a lot of attention, not only in philosophy and psychology, but in politics, journalism, jurisprudence, business, and medicine as well.
Despite spending billions of dollars on D&I initiatives, US companies are more segregated now than they were 40 years ago, and implicit bias in hiring remains one of the biggest culprits.
The task of identifying implicit premises or conclusions raises theoretical questions because there are many circumstances in which different implicit premises or conclusions can be attributed to an argument.
(Or, more exactly, since different entailment accounts will differ as to what counts as implicit content, entailment accounts have no problem with what counts as implicit ontological commitment by that account's own standards.)
The bias of crowds model is aimed at making sense of five features of implicit bias which are otherwise challenging to make sense of together, namely: (1) average group-level scores of implicit bias are very robust and stable; (2) children’s average scores of implicit bias are nearly identical to adults’ average scores; (3) aggregate levels of implicit bias at the population level (e.g., regions, states, and countries) are both highly stable and strongly associated with discriminatory outcomes and group-based disparities; yet, (4) individual differences in implicit bias have small-to-medium zero-order correlations with discriminatory behavior; and (5) individual test-retest reliability is low over weeks and months.
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The bias of crowds model is aimed at making sense of five features of implicit bias which are otherwise challenging to make sense of together namely 1 average group-level scores of implicit bias are very robust and stable 2 childrens average scores of implicit bias are nearly identical to adults average scores 3 aggregate levels of implicit bias at the population level eg regions states and countries are both highly stable and strongly associated with discriminatory outcomes and group-based disparities yet 4 individual differences in implicit bias have small-to-medium zero-order correlations with discriminatory behavior and 5 individual test-retest reliability is low over weeks and months