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The local ladder effect: Social Status and Subjective Well-Being. Cameron Anderson Michael E. Kraus Adam D. Galinsky Dacher Keltner. Income weakly influences subjective well-being. When national income increases over time, SWB does not ( Easterlin Paradox).

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the local ladder effect social status and subjective well being
The local ladder effect: Social Status and Subjective Well-Being

Cameron Anderson

Michael E. Kraus

Adam D. Galinsky

DacherKeltner

income weakly influences subjective well being
Income weakly influencessubjective well-being

When national income increases over time, SWB does not (Easterlin Paradox)

Within countries, income and subjective well-being (SWB) correlate weakly, r = .15

(e.g., Alston, Lowe, & Wrigley, 1974; Andrews & Withey, 1976; Bortner & Hultsch, 1970; Clark & Oswald, 1994;Clemente & Sauer, 1976; Diener,Haring, Stock, & Okun, 1984; Diener, Sandvik, Seidlitz& Diener, 1993; Freudiger, 1980; Horowitz, & Emmons, 1985; Inglehart, 1990; Kimmel, Price, & Walker, 1978; Mancini & Orthner, 1980;Myers & Diener1985; Nickerson et al., 2003; Riddick, 1980; Veenhoven, 1994)

status an empty pursuit
Status: an empty Pursuit?
  • Valuing money => depression and anxiety1
  • Power-oriented individuals lower in well-being2
  • Implication: Achieving status does little for SWB

1 Kasser & Ryan, 1993; Nickerson et al., 2003

2 Emmons, 1991; Sheldon et al., 2007

sociometric status
sociometricstatus
  • Sociometric status: Respectand admirationin others’ eyes1
    • It is “local,” or defined in one’s face-to-face groups
    • It is peer-determined, involving others’ respect and admiration
  • Sociometric status hierarchies emerge in all kinds of face-to-face groups2
  • Sociometric status (SMS) is empirically distinct from socioeconomic status (SES; income, education)
    • People affiliate with others of similar SES3
    • Differences in SMS emerge among individuals with same SES4
  • 1 Berger, Cohen, & Zelditch, 1972; Blau, 1964
  • 2 Bernstein, 1981; Davis & Moore, 1945; Eibl-Eibesfelt, 1989; Hogan, 1983; Leavitt, 2005; Mazur,
  • 1973; Schjelderup-Ebbe, 1935; Tannenbaumet al., 1974; Van Vugtet al., 2008
    • 3 McPherson & Smith-Lovin, 1987
    • 4Blau, 1964; Roethlesberger & Dickson, 1939; Whyte, 1943
the local ladder effect
The LOCAL LADDER effect
  • Relative, immediate comparisons matter more than absolute, distant comparisons1
    • “Beggars do not envy millionaires, though of course they will envy other beggars who are more successful” – Bertrand Russell, 1930
  • Sociometric status leads to power2, and the sense of power increases happiness3
  • Sociometricstatus leads to social acceptance4, which also increases happiness5

1 Festinger, 1954

2 Berger, Cohen, & Zelditch, 1972

3 Keltner, Gruenfeld, & Anderson, 2003

4 Thibault& Kelley, 1959

5 Baumeister& Leary, 1995

hypotheses
hypotheses
  • Local Ladder Effect: Sociometric status will shape SWB
  • The effect of sociometric status on SWB will be stronger than that of SES
overview of studies
Overview of studies
  • Study 1: College student groups, clubs,

associations

  • Study 2: National sample; mediation
  • Study 3: Experimental manipulation
  • Study 4: Longitudinal assessment of changes in

status over time

study 1 methods
Study 1: methods
  • 80 members of 12 student groups (fraternities, sororities, committees, clubs, ROTC, etc.)
    • 53% men, 47% women
    • Sociometricstatus
    • Peer-ratings of respect, admiration, looked up to (α = .71)
    • Self-ratings of status along same dimensions (r = .54, α = .93)
    • Number of leadership positions (M = 1.71, SD = 1.56)
study 1 methods1
Study 1: methods
  • 80 members of 12 student groups (fraternities, sororities, school committees, student clubs, ROTC)
    • 53% men, 47% women
    • Sociometric status
    • Peer-ratings of respect, admiration, looked up to (α = .71)
    • Self-ratings of status along same dimensions (r = .54, α = .93)
    • Number of leadership positions (M = 1.71, SD = 1.56)
  • Total household income (Adler et al., 2000)
    • (a) under $15K, (b) $15–$25K, (c) $25–$35K, (d) $35–$50K, (e) $50–$75K, (f) $75–$100K, (g) $100-$150K, and (h) over $150K
    • M = 6.17, SD = 1.44
    • Average household income between $75,000 and $100,000
study 1 methods2
Study 1: methods
  • Subjective well-being: 3 components (Diener et al., 1999)
    • Satisfaction with life scale (SWLS; Diener et al., 1985)
      • M = 5.38, SD = .94, α = .77
    • Positive and Negative Affect (PANAS; Watson et al., 1988)
      • Positive affect: M = 3.84, SD = .72, α = .89
      • Negative affect: M = 1.80, SD = .53, α = .83
  • Control for gender, ethnicity (White/non-White)
results
results
  • Sociometricstatus:

β=.35**, B=.33, SE=.10

  • Socioeconomic status:

β=.02, B=.01, SE=.06

Sociometric status predicted SWB more strongly than SES (Cohen et al., 2003), F(1,78)=14.15, p<.001

gender differences
Gender differences?
  • Several theorists have argued that men and women differ in the way they think about and are motivated by status

(Buss, 1999; Hoyenga, 1993; Sidanius, Pratto, & Bobo, 1994)

    • Men care about status more than women (Buss, 1999, p. 43)
  • Does sociometric status matter more for men’s SWB than for women’s?
  • No: For men, r = .40**, and for women, r = .38**
study 1 findings
Study 1 findings
  • Sociometric status predicted SWB (A Local Ladder Effect)
  • The relationship between sociometric status and SWB was stronger than that between SES and SWB
  • The effect of sociometric status held up for men and women
study 2
STUDY 2
  • Mediation: Why does sociometric status matter?
    • Sense of power, social acceptance
  • Focused on groups that participants chose as most important to them
    • Better gauge of the importance of sociometric status
  • More representative sample
  • Is personality a third variable? Control for extraversion
  • Measure other major component of SES: education
study 2 methods
Study 2: METHODS
  • 315 participants (36% men, 64% women) from national sample
    • Amazon.com’s Mechanical Turk: Reliable and more diverse than college samples (Buhrmeister, Kwang, & Gosling, 2010)
    • Average age = 32.8, SD = 11.0
  • Sociometric status
    • “List your three most important groups (e.g., friends, family, athletic team, work group),” rate status in each (same items as in Study 1)
    • M = 5.16, SD = .93, α = .94
  • Socioeconomic status
    • Household income: M = 4.12 ($35,001 - $50,000), SD = 1.94
    • Education: M = 2.66 (between high school and some college), SD = .75
study 2 methods1
Study 2: methods
  • Subjective well-being
    • Satisfaction with life scale: M = 4.29, SD = 1.47, α = .92
    • Positive affect: M = 3.38, SD = .78, α = .90
    • Negative affect: M = 2.08, SD = .81, α = .91
  • Control for gender, ethnicity (White/non-White)
  • Extraversion (BFI; John & Srivastava, 1999)
    • M = 3.01, SD = .82, α = .96
  • Sense of power in each group (Anderson et al., in press)
    • e.g., “If I want to, I get to make the decisions”
    • M = 4.82, SD = .75, α = .90
  • Social acceptance in each group (Leary et al., 1995)
    • accepted, included, liked, welcomed
    • M = 5.80, SD = .79, α = .96
results1
results
  • Sociometricstatus:

β=.50**, B=.43, SE=.04

  • Socioeconomic status:

β=.08, B=.07, SE=.05

Sociometric status predicted SWB more strongly than SES (Cohen et al., 2003), F(1,313)=14.13, p<.001.

sms mediation
Sms: Mediation

Sense of Power

Sobel z = 4.90, p < .01

.55** (.33**)

.57**

Sociometric Status

Subjective Well-Being

.50** (.10)

.65**

.59** (.39**)

Social Acceptance

Sobel z = 5.89, p < .01

ses no effects on sense of power social acceptance
ses: no effects on sense of power, social acceptance

Sense of Power

.55** (.56**)

-.09

Socioeconomic Status

Subjective Well-Being

.10+ (.14)

-.06

.59** (.60**)

Social Acceptance

study 2 findings
Study 2 findings
  • Sociometricstatus predicted SWB (more strongly than SES)
  • Sense of power, social acceptance mediated the link between sociometric status and SWB
  • More representative sample with wider range in SES
  • The results held up even after controlling for extraversion
  • The results held up for men (r=.54) and women (r=.48)
study 3 causation
Study 3: Causation
  • 228 participants (38% men, 62% women) via MTurk
  • 2X2 between-subjects design:
    • Status type (socioeconomic vs. sociometric)
    • Status level (low vs. high)
  • Manipulated subjective sense of SES and SMS
    • Imagine-an-interaction procedure (Kraus et al., 2010)
    • e.g., Low SES: “Imagine interacting with someone high in SES”
    • Builds from dominance complementarity principle (Horowitz et al., 2006; Tiedens, Unzueta, & Young, 2007)
socioeconomic status manipulation
SOCIOECONOMIC STATUS Manipulation

“Think of the ladder above as representing where people stand in the United States. Now please compare yourself to the people at the very bottom (top) rung of the ladder. At the bottom (top) of the ladder are the people with the least (most) money, education, and worst (best) jobs.

In particular, we'd like you to COMPARE YOURSELF TO THESE PEOPLE. Now imagine yourself in a getting acquainted interaction with one of these people. Think about how the SIMILARITIES AND DIFFERENCES BETWEEN YOU might impact what you would talk about, how the interaction is likely to go, and what you and the other person might say to each other. Please write a brief description about how you think this interaction would go.”

Blue = high socioeconomic condition

Red = low socioeconomic condition

sociometric status manipulation
SOCIOMETRIC STATUS Manipulation

“Think of the ladder above as representing where people stand in the important groups to which they belong. For example, these can include their groups of friends, family, work group, etc. Now please compare yourself to the people at the very bottom (top) rung of the ladder. These are people who have NO (A GREAT DEAL OF) RESPECTand ADMIRATIONin their important social groups.

In particular, we'd like you to COMPARE YOURSELF TO THESE PEOPLE in terms of your own respectand admiration in your important groups. Now imagine yourself in a getting acquainted interaction with one of these people. Think about how the SIMILARITIES AND DIFFERENCES BETWEEN YOU might impact what you would talk about, how the interaction is likely to go, and what you and the other person might say to each other. Please write a brief description about how you think this interaction would go.”

Blue = high sociometric condition

Red = low sociometric condition

study 3 methods
Study 3: methods
  • Subjective well-being
    • Satisfaction with life scale: M = 4.28, SD = 1.45, α = .91
    • Positive affect: M = 2.92, SD = .83, α = .91
    • Negative affect: M = 1.56, SD = .73, α = .91
manipulation check where would you place yourself on this ladder
Manipulation check:“Where would you place yourself on this ladder?”

Sociometric status

Socioeconomic status

t (115) = 3.65, p < .01

t (109) = 2.06, p < .05

No interaction: F(1,224) = 1.38, p = .24

subjective well being
Subjective well-being

Sociometric status

Socioeconomic status

t (115) = 3.05, p < .01

t (109) = .06, n.s.

Interaction: F(1,224) = 4.73, p < .05

study 3 findings
Study 3 findings
  • Sociometric status more strongly affected SWB than SES
  • Experimental methods helped establish causality
  • The effect again held up across both men and women (Interaction F[1,111] = 2.98 n.s.)
study 4
Study 4
  • When status rises or falls after a significant life transition, does SWB rise or fall accordingly?
  • In a longitudinal design MBA students were assessed:
    • One month before they graduated
    • Nine months after graduation when they had entered the workforce
  • Graduating involves moving from one sociometricstatus hierarchy to another. Such a move could involve an increase or decrease in sociometric status.
study 4 longitudinal changes in sms
Study 4: Longitudinal Changes in sms

Time 1: April 2010

Time 2: February 2011

116 (74% return rate), 71% men, 29% women

Sociometric status in workplace (α = .94)

Income (M = 6.89, SD = 1.46), $75,001-$100,000

SWB: SWLS, PANAS (all α’s> .86)

  • 156 2nd-year MBA students
  • Sociometric status in MBA cohort (α = .94)
  • Income (M = 4.89, SD = 2.82), $35,001-$50,000
  • SWB: SWLS, PANAS (all α’s> .85)
results2
results

Time 1: April 2010

Time 2: February 2011

Sociometric Status

in MBA cohort

Sociometric Status

in workplace

.46**

.00

.63**

(.40**)

Subjective Well-Being

Subjective Well-Being

.44**

Difference in sociometric status predicted difference in SWB (β=.22, p<.05).

results3
results

Time 1: April 2010

Time 2: February 2011

SES

SES

-.12

-.19*

.01

(.11)

Subjective Well-Being

Subjective Well-Being

.68**

Changes in sociometric status more strongly affected SWB, F(1,114)=20.17, p<.01.

study 4 findings
Study 4 findings
  • Changes in sociometric status predicted changes in SWB
    • As sociometric status rose or fell, so did SWB
  • Changes in sociometric status more strongly predicted changes in SWB than did changes in SES
summary
summary
  • Local Ladder Effect: Sociometric status predicted SWB (average β across correlational studies = .49)
    • Effect emerged in correlational, longitudinal, experimental designs
    • Consistent across men and women
    • Held up after controlling for demographic variables, personality (extraversion)
  • Effect of sociometric status consistently stronger than SES
  • Two underlying mechanisms:
    • Sense of power
    • Social acceptance
implications
implications
  • Status does matter to subjective well-being
    • But not all forms of status matter equally
  • Possessing higher social standing might have different psychological consequences that striving for higher standing (Nickerson et al., 2003)
  • Organizations that can raise average levels of sociometric status might promote job performance, satisfaction (Cohn, 1979; Near, Rice, & Hunt, 1978; Weaver, 1978)
future directions
Future directions
  • Why does SMS affect happiness more than SES?
    • Do people not adapt to high/low SMS, as they adapt to money?
    • SES may not lead to happiness because striving for it involves behaviors that detract from happiness. Striving for SMS involves behaviors that contribute to happiness (e.g., generosity).
  • Does the impact of SMS on happiness depend on its source?
  • What determines one’s “local ladder”?