Levin, Daniel. (2000). Race as a Visual Feature: Using Visual Search and Perceptual Discrimination Tasks to
Understand Face Categories and the Cross-Race Recognition Deficit. Journal of Experimental Psychology.
129,559-573.
Background Information
-It has been found that people have trouble recognizing members of other races.
Possible explanations are:
The lack of contact with CR (cross race) people makes one less of an expert in "coding"
their faces (is not consistently supported empirically).
Psychologically CR faces are more similar and therefore harder to be identified than are
same race faces. (The author argues these "expertise" explanations are "inadequate
because they make simplifying assumptions about face categories."
Anthony et al 1993 found that CR persons are coded emphasizing category related
information more than SR (same race) faces. (a feature selection process)
*The current hypothesis assumes that selecting race specifying information for CR faces lowers
the amount of individuating information and at the same time reduces recognition accuracy in
tasks of individuation.
The author also explains how the feature selection process supports visual and perceptual
discrimination tasks, both contradict the expertise and similarity based explanations of face
categories.
The CR recognition deficit
The cause remains a mystery in many ways mainly due to the Contact hypothesis being
inconsistently supported. Some authors argue the contact with the other race must
involve tasks of individuation to reduce the deficit. So, the perceiver must process CR faces
with the goal of individuation.
Visual Features and Categorizing Faces
Linville et al 1989 found members of out-groups to be more homogeneous than in-group
members. The author argues this concept can be carried over to perception of faces, where CR
faces are seen as having a certain feature and SR faces as not having a feature.
-Triesmman and Gorman 1988 found "visual search for feature positive target among feature
negative distracters is faster than the reverse." This is known as feature asymmetry (ex: tilted
line seen as a straight line + a tilt.) (norm feature + extra feature)
The explanation for this is that a feature positive (CR face) is easy to spot among feature
negatives (SR face) because it stands out, however a feature negative is hard to detect because
the distracters obscure the target. (To apply this to face recognition a feature negative norm
would be a SR face and a feature positive norm a CR face (norm face +CR face features).
Levin 1996 confirmed this hypothesis through a standard visual search task.
Feature-Selection Explanation for the CR recognition hypothesis.
-This hypothesis claims the deficit because race-specifying features are coded instead of
individuating information.
Anthony et al. 1992 argued that SR faces are processed with an "exemplar strategy emphasize
individual information, and CR faces are processed with a prototype strategy emphasizing
categorical information.
Experiment I
The prediction is that participants who have the deficit will be able to identify a black face
among white faces faster than a white face among black faces. Those without the deficit should
not be able to do this as well as the others.
Method: 25 participants at first
Participants who made more than 5% response errors were eliminated. (4/25 were eliminated)
18/21 participants were white
Sixteen faces from magazines were distorted to create composite faces. All faces were equal in
brightness and contrast. Faces were presented on a computer monitor.
The participants were first administered a search task where they were asked to detect the
presence/absence of a target face (either black or white). Half the time targets were absent, the
other half present. Distracters were of the opposite race of the target face. Participants hit "I"
when the target was present and "T' when it was not. Feedback was given on each answer.
Two blocks of trials were given and the race of the target was changed for each block.
Next the participants were administered an identification task which used the same two average
faces. Participants hit a "I" when the face presented was their target face.
Last was the face recognition test.
Participants were shown 16 white male faces and 16 black male faces on slides. Participants
were told their memory would be tested later and to pay attention. After viewing the set,
participants Were asked to respond with a "Y response if the face shown to them was from the set
and an "N if not.
Results
Miss rates were similar between the races, however there were twice as many false alarms for
black faces than for white faces. Non-deficit group were subjects with less or equal number of
black face false alarms as white face false alarms. The rest were put in the deficit group. The
deficit group showed a significantly asymmetry favoring black faces. Black faces were detected
significantly faster than were white faces.
Discussion
A search asymmetry favored black faces. Those with the deficit identified black faces faster than
white faces. The findings support the proposed relationship between feature selection asymmetry
and the CR recognition deficit.
Experiment 2
Purpose: To separate feature selection hypothesis from an expertise-based hypothesis by having
the participants search for inverted faces and to disconfirm the differential configural-coding
hypothesis.
Prediction: by inverting faces less individual information will be processed and therefore the
faces will be coded in a similar manner, as are CR faces.
I
Method
Procedure was similar to Experiment 1, except: display set sizes were reduced, and stimuli were
enlarged. A total of 288 trials were given. Faces were inverted by turning them 180 degrees.
Results and Discussion
A display size interaction was significant. Still visual search for black faces was faster.
Search asymmetry for black faces remained. The finding suggests differential configural coding
isn't responsible for the asymmetry. The finding also suggests that inversion disrupts configural
coding and that therefore asymmetry could be based on face specific information.
Experiment 3
Prediction: That perceptual sensitivity should be enhanced for black faces compared with white
faces when the discrimination between the two calls for race-specifying information.
Method:
Thirteen participants: 7 white, 3 Hispanic, 3 Asian, and 4 women.
A stimulus continuum between the black average face and the white average face was created
(see 566).
Participants completed two different blocks of trials, first the discrimination trials then the
categorization trials.
Discrimination trials. The participants viewed the end points (black face and white face) and were
told they would compare faces to these faces. They were shown faces and half the time was
asked if the face looked like the black face and the other half the white face. Faces presented
were separated by 20% difference on the scale. Then they chose which face looked more like the
endpoint on the face scale.
Categorization trials the endpoint faces were viewed again. The participants were then presented
one face at a time and the participant said whether the face resembled one end of the face scale or
the other more.
Results
Categorization task- The 0% to 40% faces were chosen for the black category and the 60100%
were chosen for the white category. Discrimination task- Discrimination was more accurate at
the black end.
Discussion
This experiment shows that it's possible to have more accurate perceptual discrimination for
black faces than for white faces. This supports the feature-selection hypothesis in that it
provides the assumption that “a variation in a selected feature allows improved featurerelevant discrimination” even when the discrimination allows happens in CR faces. (567).
Experiment 4
Purpose: To eliminate the possible perceptual magnet hypothesis explanation in experiment 3,
which says that discrimination is less accurate for stimuli that are similar to strong
representations (white faces).
Prediction: Sensitization should occur only for race-based discrimination between face pairs
that vary in terms of Black race-specifying information and shouldn't occur for
black end regions on the Black-Black within-race continua.
Method:
Twenty participants
Sixteen unfamiliar faces (8white, 8 black) were used.
The 8 faces were paired to make four continua (within each race), and 4 faces within each
race were paired to make 12 continua.
Discrimination task- Participants saw 2 faces for 10OOms and then one face that matched
one of these for 500ms. Then they indicated which one they saw. The 2 faces were
separated by 20%.
Classification trials- Three blocks were completed. The participants saw the end point
faces on the continuum first, then a single face and then had to say which end point face
better went with the face shown.
Results
Recognition task: Participants made many more false alarms to black faces as to white
faces, and the number of misses was virtually the same (Like in experiment 1).
Participants were categorized into deficit/no-deficit categories as they were in experiment
one.
Classification task: 0-40% and 60 - 100% were classified to the end regions.
Discrimination task: Participants with a deficit also showed improved discrimination at
the black end of the black white continuum and those with no deficit showed equally
accurate discrimination at both ends of the continuum.
Black white end regions had more accuracy with black face discrimination than when the
faces were part of the black-black continua.
Discussion
*The results support the feature selection hypothesis by showing the sensitization pattern
for black faces on the black end region of the between race continua. This also discounts
the perceptual magnetic hypothesis. The results also show that persons with the
recognition deficit choose race-specifying information to identify CR faces.
GENERAL DISCUSSION AND CONCLUSION
The results of all the experiments suggest the encoding expertise hypothesis is not correct
in by showing participants who cannot recognize black faces well can still detect and
discriminate them quickly. Experiment 2 disconfirms explanations from configural
coding differences that attempted to account for the asymmetry. In Experiments 3 and 4,
black faces resembling the black end point were discriminated more accurately only in
the between race continuum.
The feature selection explanation focuses on why people select certain features when
classifying and recognizing objects. By doing this it in a sense disproves the similarity
based models explanation for the phenomenon. The feature selection hypothesis focuses
on social cognition reasons for the phenomenon, whereas the similarity based models
look at perceptual similarities.