The Psychology of Gender 4th Edition

Methods and History of Gender Research 41

results of sex comparisons, such as income,

occupational status, and even health. Inves-

tigators should make sure they are studying

comparable groups of men and women.

Study Design: Variables Manipulated

and Measured. The experimenter can in-

fluence the outcome of a study by the vari-

ables that are manipulated and measured.

Dependent measures can be biased in favor

of males or females. A study that compares

female and male mathematical ability by ask-

ing children to make calculations of baseball

averages is biased against females to the ex-

tent that girls and boys have different expe-

riences with baseball. A study that compares

women’s and men’s helping behavior by

measuring how quickly a person responds to

an infant’s cries is biased against men to the

extent that men and women have different

experiences with children. A helping situa-

tion biased in the direction of males is assist-

ing someone with a flat tire on the side of the

road. Here, you may find that men are more

likely than women to provide assistance be-

cause men may have more experience chang-

ing tires than women. It is unlikely that men

have a “tire-changing” gene and that women

have a “diaper-changing” gene that the other

sex does not possess. Men are provided with

more opportunities to change tires just as

women are provided with more opportuni-

ties to console a crying infant. Thus, in gen-

eralizing across studies, we have to ensure

that the different ways a dependent variable

is measured do not account for the findings.

Data Collection. The experimenter can

influence the outcome of a study by how the

data are collected. The experimenter may

treat women and men differently in a way

that supports the hypothesis. In a now clas-

sic study, Rosenthal (1966) found that male

about hunches based on personal experi-

ences and desires. The best situation is one in

which the scientist conducting the research

does not care about the outcome of the study

and has little invested in it. Perhaps scientists

should be randomly assigned to topics! Most

of us do care about the outcomes of stud-

ies and are invested in those outcomes. As a

mother who works outside the home, what

would I do if I conducted a study and found

that children whose mothers worked outside

the home suffered? The task that the scien-

tist must confront is to set aside preexisting

beliefs and biases to conduct a study in as

objective of a way as possible.Replication,or

the repeating of a study, by different investi-

gators with different measures of the inde-

pendent variable and the dependent variable

helps enhance our confidence in a finding.

Study Design: Participants. The experi-

menter can influence the outcome of the

study by the participants who are chosen.

Obviously, experimenters who limit their

studies to all males or all females should

question whether their findings generalize to

the other sex. Experimenters who study both

women and men should also be sensitive to

other variables besides sex that could distin-

guish the two groups. For example, several

decades ago, an experimenter who com-

pared the mental health of men and women

might have compared employed men to

nonemployed women because most men

worked outside the home and most women

did not. If such a study showed women to be

more depressed than men, we might wonder

whether this finding was attributable to be-

ing female or to not having a job outside the

home. Today, any studies conducted of men

and women would take into consideration

employment status. There are other variables

that may co-occur with sex and influence the

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