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Red: AO3 - Evaluative points/IDAs
Suggested by Martin and Halverson, this is a similar cognitive theory to Kohlberg's theory, emphasising the active role of the child and their thinking in their gender development. However, it differs from Kohlberg's in claiming that basic gender identity is enough for a child to actively seek to observe and imitate gender-appropriate behaviour (Kohlberg had suggested that this only happens at the gender constancy phase, around age 7) , and suggesting that the development of schemas affects later behaviour, especially in terms of memory and selective attention.
GST suggests that gender develops through the formation of schemas - mental clusters of related items which together represent a concept relating to the world. Children learn schemas from information received from their parents, other children, and media such as books and television. This leads to the development of a schema of gender-appropriate behaviour - what toys to play with, what to wear, how to act and so on. Through identifying as a boy or a girl, children join an ingroup, leading them to positively evaluate their own group, and negatively evaluate outgroups (the other sex.) This motivates the child to be like their own group and to avoid the behaviour of the opposite sex, and actively seek information about their ingroup's behaviour, acquiring an ingroup schema.
This leads to the resilience of gender beliefs, where the child holds firm and rigid schemas that are resistant to change, influencing selective attention. They will ignore or misremember information that conflicts with their schemas - for example, if a boy sees a film with a male nurse, the existing schema is not altered - this schematic anomaly is ignored.
Supporting evidence for the early formation of schemas as an aspect of GST comes from a study by Campbell (2000.) A visual preference technique was used to observe babies aged 3, 9 and 18 months, finding in both sexes a preference for observing same-sex babies (more noticeable in boys) - with both genders preferring to watch "male" activities. This supports Martin and Halverson's suggestion that babies develop schemas long before they are able to speak, and that schemas drive selective attention - supporting GST's central tenet of gender ingroup formation leading to selective attention to same-sex ingroup members exhibiting gendered behaviour.
Further supporting evidence for GST comes from Poulin-Dubois et al, who asked 63 Canadian toddlers to choose a doll to carry out a series of tasks typically thought male, female or neutral. Girls aged 24 months chose the "gender-appropriate" doll, which boys did not do until 31 months. This is concordant with Cambell's findings that young children pay selective attention on a sex basis between the age of 24 and 31, far before Kohlberg's suggested age of 7 years.
However, both of these studies found gender differences between boys and girls - in Campbell's study, boys preferred to watch same-sex activities, whereas girls preferred to watch opposite-sex activities; in Poulin-Dubois et al's study, girls and boys developed the ability to identify gendered behaviour at different ages. GST claims that boys and girls develop their gender identity in the same way, so it cannot account for these differences. It would be beta bias to generalise the same developmental mechanisms to both genders, as research evidence suggests that girls and boys develop their schemas in different ways at different times.
Tenenbaum and Leaper criticised GST, claiming that it doesn't explain where schemas originate from, only their role - despite the importance of schemas - and sought to explain this aspect of GST. Carrying out a meta-analysis of 43 studies involving 10'000 participants, they looked for a relationship between the gender schemas of parents, and those of their children. They found an overall correlation of +0.16 - weak, but significant. This indicates that gender schemas are partially learnt through socialisation by parents - this correlation was too significant to be explained by chance.
Tenenbaum and Leaper's research can be considered culturally biased, taking place in predominantly Western and industrialised countries such as North America and Europe, with only 1 of 43 taking place in Asia. Bearing in mind how much parenting practices differ between cultures, it's imposing an etic to suggest that inheriting schemas from parents through socialisation is a global developmental norm - other cultures may place less emphasis as European cultures do on children growing up to be a reflection of their parents' beliefs and values.
GST helps us understand why children's beliefs and attitudes about gender roles and behaviours are so inflexible - children only pay selective attention to information that is consistent with or confirms their schemas. Therefore, if children see someone engaging in a schema-inconsistent behaviour they'll ignore or forget it.
Compared to the biological approach, this theory heavily supports the role of nurture, suggesting gender is learnt through ingroup schemas and observation/imitation of the same sex; the biological approach supports natural factors such as the influence of hormones, chromosomes and neuroanatomy as being the most important factors in gender development. Both theories have research to support them - with evidence such as the David Reimer case study supporting the role of genetics, and Campbell et al's visual preference technique supporting the role of selective attention. There is evidence for both sides of the debate, leading to the increasing popularity of the interactionalist biosocial approach, suggesting that gender is a result of both biology and environment.
This approach is based around social learning from members of same-sex ingroups, suggesting that we learn gender appropriate behaviour through the socialisation process. Kohlberg's cognitive developmental approach suggests a similar method - we pass through developmental phases of how we understand gender, but only at the stage of gender constancy experienced after the age of 7, do we pay selective attention to gendered behaviour. Although the approaches are similar, they differ strongly in this key factor, with Martin and Halverson suggesting that we have the cognitive ability to observe and imitate gendered behaviour from between two and three years old.
Friday, 18 March 2016
Social Influences on Gender
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Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs
Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs
Gender roles are learned through observation and imitation of
live and symbolic models - for example, parents, teachers, peers and the media,
who convey social messages about the importance of gender role-appropriate
behaviour. We observe their examples of gender-appropriate behaviour and then seek
to imitate them in the social learning process. Based on learning theory
principles of operant conditioning, children are seen as being positively
reinforced for behaving in gender-appropriate ways.
Socialising agents model examples of appropriate and
inappropriate behaviour, and also the consequences of conforming or not
conforming to gender norms.
Through observational learning, children acquire knowledge
regarding gender roles without actually ‘doing’ anything; children observe gender
role models being reinforced or punished for gender-appropriate and
gender-inappropriate behaviour (vicarious reinforcement) and will imitate
behaviours that they saw being reinforced and not imitate those they saw being
punished. SLT therefore explains the acquisition of gender role stereotypes in
this manner.
Gender appropriate behaviour
is reinforced by parents giving praise and toys. Fathers have been shown to
reinforce gender-appropriate behaviour more than mothers (especially in sons)
Supporting evidence comes from Lytton &
Romney (1991), who found that parents reinforced with praise and attention
stereotypical gender behaviours in both boys and girls – for example, what
activities they participated in – suggesting that social environmental factors
are important in determining gender behaviour. However, children were also
raised similarly in many ways, suggesting that reinforcement alone cannot
account for the development of gender behaviours.
Further supporting evidence comes from Fagot
& Leinbach (1995), who compared children raised in ‘traditional’ families,
where dad went to work and mum cared for children, with children raised in ‘alternative’
families, where mum and dad shared child care. At age 4, children were given
gender-labelling tasks as a means of testing gender schemas. The ‘traditional’
family children displayed more gender role stereotyping and use gender labels
earlier, suggesting that parents do act as gender role models for their
children.
TV, cinemas, magazines, music play a role in the acquisition,
shaping and maintenance of gender roles. Males tend to be more represented on
TV and tend to be in higher-status roles. Males and females portrayed in gender
stereotypical ways. Media is invasive and persistent.
Supporting evidence for the role of the media
comes from Pierce (1993) who conducted a content analysis of teenage girls’
magazines. Girls tended to be portrayed as weak and reliant on others, with a
focus on being in a relationship rather than having independent aspirations,
demonstrating the influence of the media in establishing gender attitudes and
behaviours, and supporting social learning theory’s explanation.
Peers have a strong influence, especially when children are
slightly older. Children show preferences for same-gender playmates and
segregate into same-sex groups. Peers are intolerant of gender-inappropriate
behaviour, regulating one another! Young children’s gender role stereotypes are
very rigid, but become less so as children mature.
Supporting the influence of peers in gender
development, Archer & Lloyd reported that 3-year-old children who played
the opposite sex’s games were ridiculed by their peers and ostracised,
supporting the idea that peers police gender roles. This supports the idea that children
develop an idea of what constitutes gender-appropriate behaviour from how their
peers react to behaviour, supporting the role of peers in the social learning
process.
Challenging the idea that gendered behaviour is
directly learnt from peers, Lamb & Roopnarine observed preschool children
at play and found that when male-type behaviour was reinforced in girls the
behaviour continued for a shorter time than when male-type behaviour was
reinforced in boys. This suggests that peer reinforcement mainly acts as a
reminder, rather than as a way of learning gender appropriate behaviour – the
children had already learnt the behaviours from their parents.
Compared to other explanations such as the evolutionary
and the biological approaches, theories of social influences on gender fall
firmly on the nurture side of the nature-nurture debate, explaining gendered
behaviour as a direct result of learning processes – mainly through social
learning from parents, peers and the media. This sharply opposes the biological
approach, for example, which claims that gender development results from the
influences of hormones, genetics and neuroanatomy – strongly backing the role
of nature in the debate. Both explanations have significant research evidence
to support them – for example, the case study of David Reimer for the
biological approach, the research of Lytton and Romney for the influence of
society. This has led to the increasing popularity of the interactionalist
biosocial approach, which explains gender development as an interaction between
environmental and biological processes.
Theories of social influence are primarily based
around the learning approach, ignoring other factors such as cognitions (as
suggested by Kohlberg’s cognitive developmental approach), neuroanatomy and behaviour-influencing
hormones such as testosterone (as suggested by the biological approach) and
genetics over the course of our evolutionary history (as suggested by the
evolutionary approach.) With a significant level of research support, social
influence theory can be considered strong in its own right, but fails to
account for many other factors shown to affect gender, being reductionist in
its attempt to simplify such a complex area such as gender development into the
result of simple behavioural learning processes.
Research into the effects of social influence on
gender has important real-world application in challenging certain regressive
or outdated gender stereotypes in society – changing social norms and
expectations through the portrayal of non-traditional gender stereotypes in the
media. For example, Pingree (1978) found that stereotyping was reduced when
children were shown advertisements with women in non-traditional gender roles,
leading to pressure on programme makers to use this information to challenge
attitudes. However, not all research supports the effectiveness of this
technique – Pingree found that pre-adolescent boys experienced stronger
stereotypes after being presented with examples of non-traditional gender
roles, perhaps a backlash which occurs due to boys of this age wanting to take
a view counter to that of views held by adults. Similarly, this conflicts with
gender schema theory’s suggestion that information inconsistent with our rigid
gender schemas is misremembered or ignored.
Friday, 11 March 2016
Biosocial Theories of Gender Development
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Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs
The biosocial approach takes a social constructionist approach to gender development. arguing that concepts of gender are artificial and a result of social norms rather than being an innate biological concept.
Money and Ehrhardt's biosocial theory suggests that gender development is the result of interactions between biological and sociocultural factors. Biological factors include chromosomes (XX for a female, XY for a male), and the neurodevelopmental and physical effects of prenatal hormones such as testosterone. Sociocultural factors include early socialisation based on cultural responses to biological stereotyping - this stereotyping can include the labelling of a child as a boy or a girl by parents and peers. The biological factors that lead to parental labelling as "girl" or "boy" then lead to different environments and reactions from others, which lead to gender development as boys and girls are socialised in different ways - leading to gender role identity and sexual orientation.
Eagly and Wood's social role theory suggests that psychological gender differences are a result of roles which men and women are assigned, which were a result of physical differences in our evolutionary history. For example, in our history, men were assigned the role of hunter due to their larger size - this lead to psychological, gendered characteristics such as aggression and impulsivity. Females were assigned the role of homemakers, which lead to psychological, gendered characteristics such as being empathetic and nurturing. While evolutionary theory states that selection pressures lead to physical and psychological differences which determine gender roles, social role theory suggests that physical differences lead to differently assigned gender roles, which lead to psychological differences as an aspect of gender.
Supporting evidence for the biosocial theory of gender development comes from Smith and Lloyd's 1978 study. Babies were dressed in non-gender specific clothes, then labelled with a male or female name. It was found that people would play with them in different ways according to their gender label, with boys being treated in a more physical manner. This supports biosocial theory's suggestion that initial parental gender labels (which participants believed was based on biology) affect how the child is treated and the socialisation process, providing evidence for the hypothesis that biological labels lead to different environments and social interactions, influencing gender development.
Schaffer (2004) provides further supporting evidence for the biosocial theory. A sample of 200 adults was showed a video of a 9-month-old baby, named "David" or "Dana", playing with toys and responding to stimuli. The adult labelled the baby's behaviour and emotions in gender typical ways according to whether they believed it male or female. Again, this shows that the gender identity label affects how others in society react to and stereotype the child, causing different gender development. This supports the biosocial hypothesis that biological labels as "male" or "female" lead to differential treatment from society, leading to different socialisation processes and gender development.
However, conflicting evidence for the biosocial approach comes from a study by Luxen (2007), finding sex differences in toy preferences in very young children even before socialisation can take place. This suggests that innate gender differences exist before the socialisation process - implying that gender differences are a result of pure biology rather than a reaction between biology and social environment. This challenges the approach's claim that gender role and identity is a result of socialisation based on biological sex, suggesting that nature is far more important than nurture.
The case study of David Reimer provides further conflicting evidence for the biosocial approach to gender development. Regardless of the way his parents attempted to socialise him to be psychologically female, adopting feminine traits and gender roles, upon learning his true genetic sex he rejected these attempts at socialisation and began to identify as male despite opposite parental labelling. The fact that a biological male who was socialised through toys, clothes, name and social environment as female still ultimately identified as male suggests that biology is a much more powerful force than society is in gender development, challenging the biosocial approach's claim of biological and social interactions being responsible.
The biosocial approach theoretically combines both biological and environmental factors to explain gender development, and could therefore be considered more holistic than approaches such as the evolutionary or cognitive-developmental approaches, which explain development in terms of either biology or thought processes, not both. This approach does not reduce gender development to a single, exclusive account of human behaviour. However, the majority of research points to either biological or social aspects as being the determining factor in gender development - not both! For example, Luxen's research and the case study of David Reimer firmly suggests that biology is more important than environment - no studies show an equal importance of biology and society, suggesting that a holistic explanation of gender is inaccurate.
However, in contrast to other theories such as the biological and evolutionary approaches and Kohlberg's cognitive developmental model, the biosocial theory does not explicitly favour either side of the nature-nurture debate. Instead, it assigns a role to elements of nature, through its biological sex component, and elements of nurture, through the importance of socialisation in the development of gendered behaviour. It is an interactionalist approach, unlike other approaches which could potentially oversimplify gender by explaining it as purely a result of neuroanatomy and genetics, or of cognitive processes, or of social learning.
Social Role Theory has an important real world application in lending scientific credibility towards egalitarian philosophies such as feminism, working to bring about a state of greater gender equality. Whilst approaches such as the evolutionary theory have been regarded as a force against gender equality, stating that sex differences are innate and cannot be changed by altering social contexts, the social role approach emphasises the flexibility of gender roles and behaviour. This gives it high ethical appeal because sex roles are perceived as a result of social and biological factors rather than purely biological, therefore more flexible, offering people opportunities to create and develop aspects of the self which may otherwise be constrained by typical ideas of masculinity and femininity.
Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs
The biosocial approach takes a social constructionist approach to gender development. arguing that concepts of gender are artificial and a result of social norms rather than being an innate biological concept.
Money and Ehrhardt's biosocial theory suggests that gender development is the result of interactions between biological and sociocultural factors. Biological factors include chromosomes (XX for a female, XY for a male), and the neurodevelopmental and physical effects of prenatal hormones such as testosterone. Sociocultural factors include early socialisation based on cultural responses to biological stereotyping - this stereotyping can include the labelling of a child as a boy or a girl by parents and peers. The biological factors that lead to parental labelling as "girl" or "boy" then lead to different environments and reactions from others, which lead to gender development as boys and girls are socialised in different ways - leading to gender role identity and sexual orientation.
Eagly and Wood's social role theory suggests that psychological gender differences are a result of roles which men and women are assigned, which were a result of physical differences in our evolutionary history. For example, in our history, men were assigned the role of hunter due to their larger size - this lead to psychological, gendered characteristics such as aggression and impulsivity. Females were assigned the role of homemakers, which lead to psychological, gendered characteristics such as being empathetic and nurturing. While evolutionary theory states that selection pressures lead to physical and psychological differences which determine gender roles, social role theory suggests that physical differences lead to differently assigned gender roles, which lead to psychological differences as an aspect of gender.
Supporting evidence for the biosocial theory of gender development comes from Smith and Lloyd's 1978 study. Babies were dressed in non-gender specific clothes, then labelled with a male or female name. It was found that people would play with them in different ways according to their gender label, with boys being treated in a more physical manner. This supports biosocial theory's suggestion that initial parental gender labels (which participants believed was based on biology) affect how the child is treated and the socialisation process, providing evidence for the hypothesis that biological labels lead to different environments and social interactions, influencing gender development.
Schaffer (2004) provides further supporting evidence for the biosocial theory. A sample of 200 adults was showed a video of a 9-month-old baby, named "David" or "Dana", playing with toys and responding to stimuli. The adult labelled the baby's behaviour and emotions in gender typical ways according to whether they believed it male or female. Again, this shows that the gender identity label affects how others in society react to and stereotype the child, causing different gender development. This supports the biosocial hypothesis that biological labels as "male" or "female" lead to differential treatment from society, leading to different socialisation processes and gender development.
However, conflicting evidence for the biosocial approach comes from a study by Luxen (2007), finding sex differences in toy preferences in very young children even before socialisation can take place. This suggests that innate gender differences exist before the socialisation process - implying that gender differences are a result of pure biology rather than a reaction between biology and social environment. This challenges the approach's claim that gender role and identity is a result of socialisation based on biological sex, suggesting that nature is far more important than nurture.
The case study of David Reimer provides further conflicting evidence for the biosocial approach to gender development. Regardless of the way his parents attempted to socialise him to be psychologically female, adopting feminine traits and gender roles, upon learning his true genetic sex he rejected these attempts at socialisation and began to identify as male despite opposite parental labelling. The fact that a biological male who was socialised through toys, clothes, name and social environment as female still ultimately identified as male suggests that biology is a much more powerful force than society is in gender development, challenging the biosocial approach's claim of biological and social interactions being responsible.
The biosocial approach theoretically combines both biological and environmental factors to explain gender development, and could therefore be considered more holistic than approaches such as the evolutionary or cognitive-developmental approaches, which explain development in terms of either biology or thought processes, not both. This approach does not reduce gender development to a single, exclusive account of human behaviour. However, the majority of research points to either biological or social aspects as being the determining factor in gender development - not both! For example, Luxen's research and the case study of David Reimer firmly suggests that biology is more important than environment - no studies show an equal importance of biology and society, suggesting that a holistic explanation of gender is inaccurate.
However, in contrast to other theories such as the biological and evolutionary approaches and Kohlberg's cognitive developmental model, the biosocial theory does not explicitly favour either side of the nature-nurture debate. Instead, it assigns a role to elements of nature, through its biological sex component, and elements of nurture, through the importance of socialisation in the development of gendered behaviour. It is an interactionalist approach, unlike other approaches which could potentially oversimplify gender by explaining it as purely a result of neuroanatomy and genetics, or of cognitive processes, or of social learning.
Social Role Theory has an important real world application in lending scientific credibility towards egalitarian philosophies such as feminism, working to bring about a state of greater gender equality. Whilst approaches such as the evolutionary theory have been regarded as a force against gender equality, stating that sex differences are innate and cannot be changed by altering social contexts, the social role approach emphasises the flexibility of gender roles and behaviour. This gives it high ethical appeal because sex roles are perceived as a result of social and biological factors rather than purely biological, therefore more flexible, offering people opportunities to create and develop aspects of the self which may otherwise be constrained by typical ideas of masculinity and femininity.
Kohlberg's Cognitive Developmental Theory of Gender
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Influenced by earlier theories of cognitive development
that saw children as actively progressing through developmental stages,
Kohlberg’s theory of gender development works on three principles: maturation
(children can only progress to the next stage with adequate cognitive ability
and maturity), universality (all children go through the same stages, albeit at
different times) and socialisation (children are more likely to observe and
imitate same-sex role models.) Kohlberg suggests that children understand
gender differently at different ages, actively developing an understanding of
gender from the environment, with three different stages.
Gender identity – around age 2 to 3 ½, children
understand the concept of their own sex, using the labels “boy” and “girl” in
reference to themselves or others, but do not understand that gender is stable
for life, and have very little understanding of what it means.
Gender stability – around age 3 ½, the child realises
that their sex will not change, knowing that they will grow up to be a “mummy”
or a “daddy”. However, they are still easily misled by superficial appearances
– believing that a woman cutting her hair will turn her into a man.
Gender constancy – between the ages 4 ½ to 7, the child
realises that gender is constant – people stay the same despite superficial
appearance changes. This final stage is based on Piaget’s principle of
“conservation” – the ability to know that things remain the same even after
changes in appearance.
Thompson
(1975) found that by 2 year, children given pictures of boys and girls could
select same-sex pictures, demonstrating that children could self-label and
identify the gender of others. By 3 years, 90% showed gender identity, compared
to only 76% of 2 year olds, showing the developmental nature of the concept.
Supports the age ranges that Kohlberg
suggested for each stage – Kohlberg suggested that children develop gender
identity aged 2 ½, and this is supported by the vast majority of children
having reached this stage by 3 years old – far more than had reached this stage
at 2 years.
McConaghy
(1979) found that if a doll was dressed in transparent clothing so its genitals
were visible, children of 3 to 5 years judged its gender by its clothes, not
its genitals, supporting the idea of children of this age using superficial
physical indicators to determine gender. This supports Kohlberg’s suggestion
that until age 4 ½ to 7, most children are in a stage of gender stability –
they realise that gender does not change, but are still misled by superficial
appearances such as clothing.
Rabban
(1950) found that children’s thinking changes as they age. 3 year olds
demonstrated gender identity but don’t know what gender they will grow into. By
age 5, 97% demonstrated gender stability. This supports the ages Kohlberg
suggested at which a child progresses to the stage of gender stability – around
3 ½ to 4 ½, as well as the concept of gender development as being due to
increasingly sophisticated cognitive processes with age.
Kohlberg’s theory is more
holistic than certain explanations for gender development such as the
evolutionary approach (explaining the social prevalence of gendered behaviour
as purely a result of our evolutionary history), as Kohlberg’s theory takes
into account both cognitive factors (developmental stages requiring the
cognitive ability to progress past them) and social factors (observing and
imitating same-sex models as a form of social learning. However, it can be
considered reductionist through ignoring certain aspects of human biology that
have shown to be responsible for gender development – in the case study of
David Reimer, genetic biological sex was the deciding factor in his final
gender identity despite overwhelming social factors aiming to change this.
This theory may be gender biased,
as some critics claim that females are being judged using a male standard. This
is largely because Kohlberg's original research, which he used as a basis for
this model, was done only on males. However, gender development happens
differently in males than it does in females, for example – the greater
willingness of girls to participate in masculine activities than boys to
participate in feminine activities.
Slaby and Frey’s research evidence supports the suggestion that Kohlberg’s
theory is gender biased – the gender constant girls observed the opposite sex
model more than the same sex model, while the gender constant boys did not,
suggesting that it is beta bias to assume equivalency of development between
sexes.
While Kohlberg’s theory of gender
development suggests that gender development is primarily a cognitive process,
albeit with social learning from same-sex models, other theories challenge
this, suggesting other primary factors that influence gender development. For
example, the biological approach suggests that hormones and genes are the two
most important factors in gender development – two factors of which Kohlberg’s
theory makes no mention, suggesting that gender behaviour and identity are
determined by thought processes. Additionally, the social approach to gender
explains it as a result of social reinforcement processes – seeing the child as
a passive product of the society around it rather than the active figure that
Kohlberg suggests – these theories are not completely mutually compatible, and
vary hugely in their approach to how we develop gender.
Ethics in Psychological Research
You will often be asked to identify ethical issues in a given study and asked how they can be addressed - remember to refer to the source to look at possible issues in the methodology such as deception and failure to protect participants from harm.
Black: AO1 - Description of an ethical issue.
Red: AO2/3 - Way of dealing with an ethical issue.
Informed consent – participants should agree to be in an experiment after being made aware of the aim of the experiment and their role in it. Before giving their consent, they must be made aware how data are collected, what exactly they’re doing in the experiment, and, in an independent groups design, they must be made aware what those in the other condition are doing. The research must fully explain the experiment's duration and methodology, as well as the expected benefits to society of the research and any potential risks and discomforts to the participant.
Deception - participants should not be deceived as to their role in the experiment. This includes active deception through lying to them, and passive deception through just withholding information and not being outright with everything they’re entitled to be told.
Black: AO1 - Description of an ethical issue.
Red: AO2/3 - Way of dealing with an ethical issue.
Informed consent – participants should agree to be in an experiment after being made aware of the aim of the experiment and their role in it. Before giving their consent, they must be made aware how data are collected, what exactly they’re doing in the experiment, and, in an independent groups design, they must be made aware what those in the other condition are doing. The research must fully explain the experiment's duration and methodology, as well as the expected benefits to society of the research and any potential risks and discomforts to the participant.
Deception - participants should not be deceived as to their role in the experiment. This includes active deception through lying to them, and passive deception through just withholding information and not being outright with everything they’re entitled to be told.
However, in some areas of research it is not always possible to get informed consent, and necessary to deceive participants - in certain studies into social influence, the participant must be unaware that they are in a study, so that demand characteristics don't invalidate the results. In this scenario, there are other ways in which consent can be obtained:
- Prior general consent - asking for consent beforehand when explaining the general area of research, asking if they feel comfortable and consent to taking part to research in that area and possibly being deceived - without mentioning a specific form of deception.
- Presumptive consent - take another sample from the target population and ask them if they'd consent to the study - if they all would, presume that your experimental sample would too.
- Colleague consent - ask other professionals if they thought participants would give informed consent to the study - if they think so, carry out the research presuming consent from this.
- Ethics committees - talk a committee of psychologists and non-psychologists through your methodology, outlining any issues that may arise, the purpose and procedure of the research, and seek approval from them before seeking general consent.
Debriefing - after the study has concluded, address any questions and concerns participants may have towards the purpose and procedure of the research, reassure participants that their results will be kept confidential, remind them of their right to withdraw and remind them of everything covered under informed consent regulations.
Confidentiality – the data should not allow
readers to identify individual participants – all names, addresses, dates of
birth and other identifying information should be removed so that the remaining
data is completely anonymous.
Right to withdraw – participants should be told
at the start of the experiment that they can withdraw whenever they want to,
their results will not be published, and they can take any money that they are
entitled to. They must be reminded of this right throughout, at the end of the
experiment, and during the debriefing. Participants should not be pressured to continue if the study is causing them distress, as was the case in Milgram's famous study of obedience.
Protection: The participant should not experience any more harm or distress over the course of the study than they might reasonably expect carrying out day-to-day activities. The researchers should ensure that the participants do not leave the experiment in a worse psychological or physical state than when they started.
Protection: The participant should not experience any more harm or distress over the course of the study than they might reasonably expect carrying out day-to-day activities. The researchers should ensure that the participants do not leave the experiment in a worse psychological or physical state than when they started.
Tuesday, 8 March 2016
Explanations of Gender Dysphoria
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Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs
Blue: AO2 - Research
Red: AO3 - Evaluative points/IDAs
A psychosocial explanation, mental illness theory suggests
that gender dysphoria is related to mental illness, which is in turn a result
of childhood trauma or maladaptive upbringing. Coates et al (1991) carried out
a case study of a boy who developed gender dysphoria, claiming that this was
his response to his mother’s post-abortion depression. The trauma occurred when
the boy was three – a time when children are particularly sensitive to gender
issues – and Coates et al suggested that the trauma led to a cross-gender
fantasy as a means of resolving anxiety.
Cole et al (1997) studied 435
individuals experiencing gender dysphoria and reported that the range of
psychiatric conditions displayed was no greater than found in a non-dysphoric
control group; challenging mental illness theory’s suggestion that gender
dysphoria is related to trauma or psychological pathology.
Irregularities in mother-son relationship are another
factor suggested to contribute to the development of gender dysphoria. Stoller
(1975) proposed that GID results from distorted parental attitudes – in
clinical interviews with individuals diagnosed with GID, they displayed overly
and atypically close mother-son relationships; he suggested that this led to
greater female identification and a confused gender identity.
Zucker et al (1996) studied
boys with concerns about gender identity and their mothers. Of the boys who
were eventually diagnosed with GID, 64% were also diagnosed with separation
anxiety disorder, compared to 38% in the boys with subclinical GID symptoms.
This supports Stoller’s suggestion of abnormal maternal attachment as a factor
in gender dysphoria, but can only explain MtF (Male to Female) transsexuality –
it does not suggest an explanation for FtM.
A biological theory of gender dysphoria, the brain-sex
theory suggests that male and female brains are structurally different, and the
brains of transsexuals do not match their genetic sex. A region of the brain
called the BSTc, located in the thalamus, is twice as large in heterosexual men
as in heterosexual women, and contains twice the number of neurons – and in
transsexuals, BSTc size correlates with psychological gender, rather than
biological sex, suggesting a mismatch between the brains and biological sexes
of transsexuals.
Two research studies support
this theory: Zhou et al (1995) and Krujiver et al (2000) found that the number
of neurons in the BSTc of MtF transsexuals was similar to those of biological
females, while the number of neurons in the BSTc of FtM transsexuals was
similar to those of biological males. This supports the theory’s explanation of
gender dysphoria as having a mismatch between chromosomal sex and psychological
gender.
However, Chung et al (2002)
provided powerful conflicting evidence for this theory – finding that the
differences in BSTc volume between males and females do not emerge until
adulthood – whereas most transsexuals experience their feelings of gender
dysphoria to begin in early childhood. This suggests that the differences in
the BSTc reported by Zhou and Krujiver could not be the cause for gender
dysphoria, but rather a possible effect.
Additionally, Hulshoff Pol et
al (2006) found that transgender hormone therapy does affect the size of the
BSTc, and the individuals in Zhou and Krujiver’s studies had been receiving
hormone therapy. Therefore, it may be that the hormones caused the finding in
transsexuals that their brain sex was closer to their gender identity than
their biological sex, challenging the validity of the supporting evidence.
There is other evidence to
support the theory of gender dysphoria as a result of neuroanatomical
abnormalities – Rametti et al (2011) studied the brains of FtM transsexuals
before they started transgender hormone therapy, and found amounts of white
matter more closely resembling individuals of their gender identity than of
their biological sex.
Environmental effects have also been suggested as a
biological factor that can contribute to the development of gender dysphoria –
environmental pollutants such as DDT contain oestrogens which may mean that
males are exposed to abnormally high levels of female hormones during gestation,
causing a mismatch between genetic sex and hormone-influenced gender identity.
A study by Vreugdenhil et al
(2002) supports this explanation of gender dysphoria, finding that boys born to
mothers exposed to dioxins, a chemical class promoting oestrogen production,
displayed more feminised play than a control group, suggesting that
environmental chemical factors can lead to a mismatch between gender identity
and genetic sex.
Blanchard proposed two distinct
subcategories of transsexuality: “homosexual transsexuals”, who wish to change
biological sex because they are attracted to their current biological sex (e.g.
a homosexual male who wishes to transition to female) and “non-homosexual
transsexuals” who wish to change sex because they are “autogynephilic” –
attracted to the idea of themselves as the other sex. These groups are so
different that it is impossible to presume that the dysphoria has the same root
cause – suggesting that there are different explanations for different types of
gender dysphoria.
There are ethical issues with
research into dysphoria, namely that it is an extremely socially sensitive area
of research, with potentially huge social consequences for individuals
represented by the research. For example, if a biological cause is identified
this might help others to become more accepting of transsexuals, understanding
that it is not their fault, or it may cause individuals born with the
biological cause present to be harmed or neglected, because it might be
incorrectly assumed that future transsexualism is inevitable. Evidence from
research suggests that a simple deterministic cause and effect relationship is
unlikely – either way, the outcome has important social consequences for
sufferers of gender dysphoria.
There is important real-world
application of these explanations of gender dysphoria. Colapinto (2000) reports
that 1 in 2000 people are born with anomalous genitals that do not match their
genetic sex, and research into gender dysphoria is very important in determining
the effect of such anomalies and determining the best solutions. Societies such
as the “Organisation Intersex International” argue that our society must place
less emphasis on biological sex and recognise gender characteristics as a
social construction to allow intersex individuals to determine their own gender
identity – psychological research is important to supply research evidence to
support or challenge such arguments.
Cole (1997) found that MtF
transsexuals scored much differently in the masculinity-femininity scale of the
MMPI to FtM transsexuals or a control group without GID. Additionally, the
incidence of MtF gender dysphoria has been found to be much higher than FtM
gender dysphoria. These differences in the way the sexes experience gender dysphoria
suggests that it is beta gender bias and an oversimplification to assume
equivalence of origin in both genders – current theories don’t explain why
biological males experience GID differently and more often than biological
females; a more accurate theory should explain these differences.
Friday, 4 March 2016
Psychological Reports and Peer Review
Black - AO1 - Description
Red - AO2/3 - Evaluation
When psychological journal articles are published, they have an abstract - a brief summary of the research, outlining the aim, hypothesis, method, results and conclusion. This helps the reader decide whether the research is relevant to what they're trying to find out, and whether they should read on.
Psychological research has practical applications and practical implications. Practical implications are what we can infer and interpret from the results of the research - what it adds to our understanding of a field of psychology. Practical applications are how the findings and conclusions can be used in a real-life scenario - ways in which the research can beneficially change how people behave.
The peer review process involves other knowledgeable psychologists studying similar topics reviewing the researcher, assessing the credibility, the legitimacy and the accuracy of the research. This serves several purposes.
Red - AO2/3 - Evaluation
When psychological journal articles are published, they have an abstract - a brief summary of the research, outlining the aim, hypothesis, method, results and conclusion. This helps the reader decide whether the research is relevant to what they're trying to find out, and whether they should read on.
Psychological research has practical applications and practical implications. Practical implications are what we can infer and interpret from the results of the research - what it adds to our understanding of a field of psychology. Practical applications are how the findings and conclusions can be used in a real-life scenario - ways in which the research can beneficially change how people behave.
Peer Review
The peer review process involves other knowledgeable psychologists studying similar topics reviewing the researcher, assessing the credibility, the legitimacy and the accuracy of the research. This serves several purposes.
- To verify the academic integrity of the researcher - that they aren't plagiarising other academics, and are giving appropriate credit to the authors of their sources.
- To check that appropriate statistical tests have been used for the level of the data and experimental design chosen.
- To check that legitimate, valid conclusions and interpretations have been drawn from the results - ascertaining that results have not been misinterpreted.
- To make sure that findings are novel and contribute to a broader body of knowledge in its field - rather than a simple replication of research already carried out in the same social and historical context.
- To make sure that the researcher is not making unjustified claims about the importance and social significance of their research.
- To make sure that any ethical issues that arose over the course of the research were handled appropriately, and that the BPS ethical guidelines were adequately followed.
- To ensure that all research is reviewed by fellow experts, maintaining academic standards of research - so poor quality research is not published in reputable journals.
- Peer review is time consuming and expensive - it can take months or years for research to be reviewed and published, delaying the publication of important findings.
- Reviewers usually work in the same field as the author of the research - there could be an incentive to delay the publication of their rivals' important findings, especially when financial research grants are at stake.
- There is a bias towards more well-respected and prestigious institutions and researchers - papers from these are more likely to be approved simply due to the renown of the institution or individual, even if they are of no higher standard of academic integrity than research from a less prestigious one.
- There is a tendency to favour the scientific status quo - research which supports the commonly accepted scientific theories and approaches at the time of its review is more likely to be considered valid and to be approved than research which challenges the established scientific consensus. Peer review may slow down the revolution from one scientific paradigm to another.
- Review may be biased through the reviewer's personal, subjective views differing from those expressed in the submitted report - e.g, if the reviewer is convinced that intelligence is highly genetic, they may look unfavourably upon research that suggests a role for environmental factors in intelligence, and reject research papers that suggest this.
- The "file drawer phenomenon" - peer review tends to favour positive results that support the hypothesis rather than those which challenge the hypothesis or support a null. Many negative or null findings are simply not published - left in the researcher's file drawer. This biases our understanding of a topic towards supporting theories that might not consistently be supported by research, but only the supporting evidence is published.
Inferential and Descriptive Statistics, Data Levels, Significance and p-Values
If unsure on the types of hypothesis and what they predict, I'd suggest reading this post: http://samsa2psych.blogspot.co.uk/2016/02/hypotheses-sampling-and-design.html before trying to get your head around inferential statistics!
Descriptive statistics help us draw conclusions from the results of a set of data, giving a typical score. They are divided into measures of central tendency and measures of dispersion.
Measures of central tendency such as the mean (add all the values up, divide by number of values), median (arrange the values in numerical order, take the one in the middle) and mode (most common value.)
Measures of dispersion give a spread of results, suggesting the consistency of the values that make up our results. These include range (difference between highest and lowest value), interquartile range, and standard deviation.
Inferential statistics tell us the probability of differences in our results being due to direct IV manipulation (an alternative hypothesis = a causal link between the IV and the DV) rather than through chance or extraneous variables. The inferential test used depends on the experimental design and the level of data collected - data can be classified as one of three types.
Nominal level data - the most basic form, named categories. We know little other than what category a result fits into. For example, measuring height using nominal level data could be done through two categories: "above 6ft" and "below 6ft"
Ordinal level data (rank measurement)- data is ordered from highest to lowest value. We don't know the gaps and boundaries between rankings (parameters) but we know what order results come in. For example, measuring height using ordinal level data would be done by arranging results in order of highest to lowest value.
Likert scales are an example of ordinal data - a participant is given a statement and asked how much they agree or disagree with it - a response of "4" means that they agree more than a response of "2" - but we do not know how much more - it lacks parameters.
In Milgram's study of conformity, he measured the maximum voltage electric shock the participants would give to a confederate - but this data is only "at least ordinal" - administering 200V did not necessarily make participants twice as conforming as administering 100V, or half as conforming as administering 400V.
Interval level data - we know that gaps and boundaries between data, and the parameters are scientifically equivalent. For example, measuring height in metres and centimetres. Ratio level data is a type of interval data starting at 0 - for example, height.
Metrics such as words remembered from a list are also not necessarily interval level data - it is unclear how much each word remembered represents a better memory - someone who can remember 10 words does not necessarily have only twice as good a memory as someone who can remember 5.
In cases such as the above, we say the data is at least ordinal level, and treat it accordingly - when it is ambiguous as to whether the data is ordinal or interval.-
Once we have established the level of the data collected, we select an appropriate test to calculate the statistical significance of the results.
Repeated Measures/Matched Pairs Independent Groups Correlational
Nominal Binomial Sign Test Chi-Squared Chi-Squared
Ordinal Wilcoxon Signed Ranks Mann-Whitney U Spearman's RHO
Interval Related t-Test Unrelated t-Test Pearson's
These tests give us a p-value, a measure of the probability that our results are due to chance/EVs rather than IV manipulation (validating the alternative hypothesis). Our calculated p-values are compared to a number ranging from 0 to 1.0 to judge its significance. (The "critical value")
p ≤ 0.10 means that the probability that results are due to chance (p) is less than or equal to 0.1 (10%) - meaning that the probability of the results being due to IV manipulation is greater than or equal to 90% - if our p-value is less than 0.10, we can be 90% certain that the alternative hypothesis is valid.
Generally, in psychology, we measure significance by p ≤ 0.05 - p is less than 5%, meaning that for results to be statistically significant, we must be 95% sure that they are due to IV manipulation, not chance. The value that p must be less than is our "critical value" - required for significance. This is a fairly stringent measurement of significance - although sometimes p ≤ 0.01 is used - 99%.
A type 1 error occurs when we are led to incorrectly thinking that there is a significant difference, and accepting our alternative hypothesis, when in fact there is not a significant difference, and our hypothesis is incorrect. We incorrectly reject a null hypothesis. This is done by setting the required significance value too high (e.g. p ≤ 0.2 means 20% chance that results are due to chance is still counted as statistically significant) - and having a p-value lower than this significance level. The more stringent our level of significance, the less chance of making a type 1 error. At p ≤ 0.01, the chance of a type 1 error is 1% or less.
A type 2 error occurs when we are led to incorrectly believing that there is no significant difference where one does actually exist, and rejecting our alternative hypothesis despite it being valid and correct. We incorrectly accept a null hypothesis. This is done by setting the required significance value too low (e.g. p ≤ 0.01 means only 1% or less chance that results are due are chance are counted as significant - 98.9 % chance of alternative hypothesis being correct is rejected as insignificant - 99% is required for significance) and having a p-value higher than the significance level. The more stringent our level of significance, the greater chance of making a type 2 error.
Answering questions on this, refer to three points in your answer - the calculated p value, the value required to indicate significance (critical value), and the degree of significance - if, to be significant, the critical value is 0.05, then we have a fairly high degree of significance when p ≤ 0.05 - the probability that our results are due to IV manipulation rather than chance or EVs is greater than or equal to 95%. This would be phrased by writing "this result is significant at the p≤0.05 level"
Some inferential statistical tests have significance values work in the opposite way, with the calculated value needing to be greater than the critical value for significance. This will be told to you in the question if this happens.
Descriptive Statistics
Descriptive statistics help us draw conclusions from the results of a set of data, giving a typical score. They are divided into measures of central tendency and measures of dispersion.
Measures of central tendency such as the mean (add all the values up, divide by number of values), median (arrange the values in numerical order, take the one in the middle) and mode (most common value.)
Measures of dispersion give a spread of results, suggesting the consistency of the values that make up our results. These include range (difference between highest and lowest value), interquartile range, and standard deviation.
Inferential Statistics
Inferential statistics tell us the probability of differences in our results being due to direct IV manipulation (an alternative hypothesis = a causal link between the IV and the DV) rather than through chance or extraneous variables. The inferential test used depends on the experimental design and the level of data collected - data can be classified as one of three types.
Nominal level data - the most basic form, named categories. We know little other than what category a result fits into. For example, measuring height using nominal level data could be done through two categories: "above 6ft" and "below 6ft"
Ordinal level data (rank measurement)- data is ordered from highest to lowest value. We don't know the gaps and boundaries between rankings (parameters) but we know what order results come in. For example, measuring height using ordinal level data would be done by arranging results in order of highest to lowest value.
Likert scales are an example of ordinal data - a participant is given a statement and asked how much they agree or disagree with it - a response of "4" means that they agree more than a response of "2" - but we do not know how much more - it lacks parameters.
In Milgram's study of conformity, he measured the maximum voltage electric shock the participants would give to a confederate - but this data is only "at least ordinal" - administering 200V did not necessarily make participants twice as conforming as administering 100V, or half as conforming as administering 400V.
Interval level data - we know that gaps and boundaries between data, and the parameters are scientifically equivalent. For example, measuring height in metres and centimetres. Ratio level data is a type of interval data starting at 0 - for example, height.
Metrics such as words remembered from a list are also not necessarily interval level data - it is unclear how much each word remembered represents a better memory - someone who can remember 10 words does not necessarily have only twice as good a memory as someone who can remember 5.
In cases such as the above, we say the data is at least ordinal level, and treat it accordingly - when it is ambiguous as to whether the data is ordinal or interval.-
Types of Inferential Statistical Test
Once we have established the level of the data collected, we select an appropriate test to calculate the statistical significance of the results.
Repeated Measures/Matched Pairs Independent Groups Correlational
Nominal Binomial Sign Test Chi-Squared Chi-Squared
Ordinal Wilcoxon Signed Ranks Mann-Whitney U Spearman's RHO
Interval Related t-Test Unrelated t-Test Pearson's
These tests give us a p-value, a measure of the probability that our results are due to chance/EVs rather than IV manipulation (validating the alternative hypothesis). Our calculated p-values are compared to a number ranging from 0 to 1.0 to judge its significance. (The "critical value")
p ≤ 0.10 means that the probability that results are due to chance (p) is less than or equal to 0.1 (10%) - meaning that the probability of the results being due to IV manipulation is greater than or equal to 90% - if our p-value is less than 0.10, we can be 90% certain that the alternative hypothesis is valid.
Generally, in psychology, we measure significance by p ≤ 0.05 - p is less than 5%, meaning that for results to be statistically significant, we must be 95% sure that they are due to IV manipulation, not chance. The value that p must be less than is our "critical value" - required for significance. This is a fairly stringent measurement of significance - although sometimes p ≤ 0.01 is used - 99%.
A type 1 error occurs when we are led to incorrectly thinking that there is a significant difference, and accepting our alternative hypothesis, when in fact there is not a significant difference, and our hypothesis is incorrect. We incorrectly reject a null hypothesis. This is done by setting the required significance value too high (e.g. p ≤ 0.2 means 20% chance that results are due to chance is still counted as statistically significant) - and having a p-value lower than this significance level. The more stringent our level of significance, the less chance of making a type 1 error. At p ≤ 0.01, the chance of a type 1 error is 1% or less.
A type 2 error occurs when we are led to incorrectly believing that there is no significant difference where one does actually exist, and rejecting our alternative hypothesis despite it being valid and correct. We incorrectly accept a null hypothesis. This is done by setting the required significance value too low (e.g. p ≤ 0.01 means only 1% or less chance that results are due are chance are counted as significant - 98.9 % chance of alternative hypothesis being correct is rejected as insignificant - 99% is required for significance) and having a p-value higher than the significance level. The more stringent our level of significance, the greater chance of making a type 2 error.
Answering questions on this, refer to three points in your answer - the calculated p value, the value required to indicate significance (critical value), and the degree of significance - if, to be significant, the critical value is 0.05, then we have a fairly high degree of significance when p ≤ 0.05 - the probability that our results are due to IV manipulation rather than chance or EVs is greater than or equal to 95%. This would be phrased by writing "this result is significant at the p≤0.05 level"
Some inferential statistical tests have significance values work in the opposite way, with the calculated value needing to be greater than the critical value for significance. This will be told to you in the question if this happens.
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