Sentence examples for gender inference from inspiring English sources

Some other topics of study include the understanding of city dynamics [8, 20, 21], event detection/study [22 27], cultural differences [7, 10, 28 30], and gender inference [31 33].

However, there were notable distinctions in the relationship between gender, facial inference and voting behavior in current simulated Presidential election outcomes versus actual Congressional election outcomes.

Finally, in our study we investigated only women, in order to rule out effects of gender, therefore our inferences and conclusions cannot be generalized to male subjects.

Higher levels of estrogen, estradiol, prolactin and hCG have previously been reported in NVP and HG pregnancies, suggesting causal inference regarding gender and NVP [ 6, 9, 17, 26, 56], although the issue remains speculative.

While the current findings demonstrate gender biases in facial inferences that affect voting behavior, as women become an increasingly visible presence in electoral politics and government, voters may learn to reduce their reliance on cognitive shortcuts, such as gender stereotypes and intuitive heuristics [10].

However, inferences about gender differences in relation to deprivation and mortality are sensitive to the choice of inequality measures used [ 34- 36].

One of the richest and most powerful tools in social communication is the face, from which observers can quickly and easily make a number of inferences — about identity, gender, sex, age, race, ethnicity, sexual orientation, physical health, attractiveness, emotional state, personality traits, pain or physical pleasure, deception, and even social status.

We will develop our own plan of action to protect voting rights, civil rights, police reform and other issues of grave concernAnd we have observed gender inequality, Islamophobia, stereotyping, racial inferences and very clear ways of marginalizing certain groups of people.

Where numbers were large enough for valid statistical inference, groups were stratified by gender.

Participants of the Health2000 survey (N = 5000) were used as age and gender matched population controls to avoid biased inferences.

Second, we did not gather subjects' demographic information such as age and gender which may have helped to make inferences from the data.