Factors affecting attraction: filter theory Flashcards
who proposed filter theory
kirckhoff and davis (1962)
what is filter theory
An explanation for relationship formation. It states that a series of different factors progressively reduces the range of available romantic partners to a much smaller pool of possibilities.
- social demography,
- similarity in attitudes
- complementarity.
Factors act as features to narrow down our partner choice to field of desirables
Social demography (1st level of filter)
Geographical location, social class, level of education, ethnic group and religion. You are more likely to meet people who share several demographic characteristics. A partner who is too different is discounted, outcome of this filtering is homogamy (more likely to form relationship with someone socially or culturally similar).
Similarity in attitudes (2nd level of filter)
Partners will often share important beliefs and values, partly because the field of availables has already been narrowed by the first filter to those who have significant cultural and social values in common. Kerckhoff and Davis found that similarity of attitudes was important to the development of romantic relationships, but only for couples who had been together less than 18 months. There is a need for partners in the early stage of a relationship to agree over basic values. If no similarity in attitudes relationship will fizzle out.
Complementarity (3rd level of filter)
The ability of a romantic partner to meet each others needs. Two partners complement each other when they have traits the other lacks. Like making the other laugh. K + D found that the need for complementarity was more important for long term couples. It is attractive as it gives the feeling that they form a whole.
Evaluation of filter theory (brief)
strength - research support from K+D original study, however levinger
weakness - comp not central to all long term relationships
weakness - perceived similarity more important
strength of filter theory
there is research support from Kerckhoff and Davis’s original study. Kerckhoff and Davis’s original longitudinal study in which partners in dating couples completed questionnaires to assess similarity of attitudes/ values and complementarity of needs. Relationships closeness was measured by another questionnaire seven months later. Closeness was associated by similarity of values but in only those who had been together less than 18 months. Complementarity of needs predicted closeness in longer relationships. This study provided evidence that similarity is important in the early stages of relationships, but complementarity is more important later on. However, Levinger pointed out many studies failed to replicate these findings. He put this down to social change also to problems in defining the depth of a relationship in terms of its length. The 18-month cut off to distinguish short and long term relationships assumed that those together longer were more committed. This is a questionable assumption which means that filter theory is undermined by the lack of validity of its evidence base.
weaknesses of filter theory
Complementarity may not be central to all longer term relationships. A prediction of this theory is that in the most satisfying relationships partners are complementary. Markey and Markey found lesbian couples of equal dominance were the most satisfied. Their sample of couples had been romantically involved for a mean time of more than 4 1/2 years. This suggests similarity of needs rather than complementarity may be associated with long term satisfaction.
Actual similarity matters less in a relationship than perceived similarity. Meta analysis by Montoya et al found that actual similarity affected attraction only in very short-term lab based interactions. In real world relationships perceived similarity was a stronger prediction of attraction. One interpretation of this finding is that partners may perceive greater similarities as they become more attracted to each other. Therefore perceived similarity may be an effect of attraction and not a cause, which is not predicted by the filter model.
