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Posted on April 27th, 2014, by

Participants

Sampling was done for English-speaking or Spanish-speaking participants of 18+ years old, living in the US, in non-institutional arrangements. 2,044 participants took part in the GSS 2010 survey, their mean age was 46.64 years old, SD = 17.36, minimal age of participants was 18 years, maximal age ”“ 89 years. There were 54.8% of females and 45.2% of males among the participants. There were 75.5% of participants who listed their race as White, 14.6% of participants who listed their race as Black, and 9.7% of participants who indicated Other race.

Instruments and procedures

The survey took place in the form of interviews. Median interview length for GSS 2010 constituted 1.5 hours. For the purpose of this research, the following variables of the GSS 2010 survey were included: “feels discriminated because of age”¯ (1 ”“ yes or 0 ”“ no responses), “feels discriminated because of gender”¯ (1 ”“ yes or 0 ”“ no responses), ), “feels discriminated because of race”¯ (1 ”“ yes or 0 ”“ no responses), and the “general happiness variable”¯. The question posed in the survey was “Taken all together, how would you say things are these days – would you say that you are very happy, pretty happy, or not too happy?”¯, with variable levels being 1 ”“ very happy, 2 ”“ pretty happy, and 3 ”“ not too happy. These values were then recoded into 0 ”“ not happy (from former 3 value), and 1 ”“ happy (from former 1 and 2 values).

Since all variables included in the model were binary, logistic regression method was chosen for determining whether there was a significant relationship between one or several discrimination-related variables and the level of overall happiness.

Results

Descriptive statistics for all four variable included in the research is shown in Table 1.

Feels discriminated because of age

Feels discriminated because of gender

General Happiness

Feels discriminated because of race

N Valid

1162

1161

855

1162

Missing

882

883

1189

882

Mean

.0766

.0500

.6292

.0568

Median

.0000

.0000

1.0000

.0000

Mode

.00

.00

1.00

.00

Std. Deviation

.26606

.21795

.48329

.23156

Range

1.00

1.00

1.00

1.00

Table 1. Descriptive statistics for experimental variables

Significance level was chosen as 0.05 for this research. The results of logistic regression are shown in Table 2.

B

S.E.

Wald

df

Sig.

Exp(B)

Step 1 Feels discriminated because of age

-.574

.390

2.161

1

.142

.563

Feels discriminated because of race

-.935

.522

3.216

1

.073

.392

Feels discriminated because of gender

-.079

.467

.029

1

.865

.924

Constant

.750

.103

52.648

1

.000

2.116

Table 2. Results of logistic regression

Nagelkerke R square for the model is 0.023, which means that only 2.3% of variation in overall happiness in the experimental data could be explained by changes of independent variables. This low value shows that the model is not effective, and it is not possible to state that there is a significant relationship between either of workplace discrimination variables and general level of happiness.

For the variable “Feels discriminated because of age”¯ p-value is .142, for the variable “feels discriminated because of race”¯ p-value is .073, and for the variable “feels discriminated because of gender”¯ p-value is .865. All three values are greater than significance level of 0.05, which means that for neither of this variable, the relationship with the dependent variable can be deemed significant. However, the variable “feels discriminated because of race”¯ was close to the significance level, and it would be reasonable to pay higher attention to race discrimination in future variations of this research.

Overall, null hypothesis cannot be rejected, and it is possible to state that in this experiment no significant relationship between any of workplace discrimination variables and general happiness variable was detected.

Discussion

The results indicated that there was no statistically significant relationship between either of three components of workplace discrimination and overall happiness level. However, survey data showed that among 2,044 respondents, only 477 cases were included in analysis because all variables values were present; for 1,567 cases, one or several variable values were missing. This means either that people were not inclined to answer these questions, or could have been confused by the formulation of the questions. Descriptive statistics shows that the variable causing major issues was the general happiness ”“ only 855 respondents have provided valid responses. Most likely, this question needs to be reworded or even separated into a series of questions addressing happiness in different spheres of life.

Thus, the results of the research might have been statistically insignificant due to survey design and lack of responses associated with both dependent and independent variables. As a continuation of this experiment, it is recommended to include the concept of workplace satisfaction as a separate dependent variable in the research, and specify the notion of happiness (according to different spheres of human life). Such changes in research design might lead to more significant statistical results, compared to the current experiment.

Furthermore, independent variables in the survey (“feels discriminated because of age/gender/race”¯) are quite subjective, and it might happen that respondents would deny (or get used to) indirect discrimination, which could affect the results of their happiness as a confounding variable. Thus, it would be reasonable to evaluate the level of workplace discrimination independently in different regions, compare the perceptions of discrimination with more objective estimates of workplace discrimination, and measure the relationship between external estimates of workplace discrimination, subjective estimates of workplace discrimination and overall workplace satisfaction and happiness level.

 

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