Begging for Change: A Comparative Analysis of How the Media Frames Domestic and International Poverty

Conclusion

The function of this research project was to explore the similarities and differences in how both domestic and international poverty are framed by the most circulated news magazine in the U.S, and to recognize how this framing may impact public opinion and policy. As a whole, coverage of poverty is rare. As well, coverage of international poverty is three times more common than coverage of domestic poverty. This frames poverty as a much more prevalent problem outside of our country’s borders.

Much of United States media today has been consolidated, and approximately 90% is owned by the ‘Big Six’. These Big Six corporations include General Electric, Walt Disney, News Corp., Time Warner, Viacom and CBS (Ownership Chart). Conflict theory argues that power differentials in capitalist societies, such as the United States, result in the dominant elite pushing their views and goals onto the general public for financial gain and status maintenance (Ashley and Ornstein 2005: 195-199). Applying this to the media, the six elite corporations are able to control what and how issues, including poverty, are covered and framed. In doing this, they are able to manage the media to best serve the needs of the upper class, elite corporations and individuals.

This elitist framing can be tied in with agenda setting theory, a communications theory that explains that the media has the power to strongly influence which issues are important to the public. The extent to which the media covers an issue determines whether the public views the issue as something that concerns them or not. Further, the concerns and opinions of the public shape policy and political agenda (Mortensen 2010: 357). As an overwhelming majority of United States media is controlled by a small number of elite corporations, these corporations are able to dictate public opinion, hence, directly sway and control public policy. Frequently and more accurately covering poverty may draw negative attention to those in power, and urge others to help those in poverty, which would not directly benefit the United States’ upper class and corporations. So, the media instead covers more timely matters and current events, paired with pervasive problems that may have a more positive benefit for the elite. Through this misframing of reality and events, the public is led to hold misperceptions on poverty’s presence in the U.S., and therefore, public policy and action will be based off of wrong premises (Johansson 2007: 277).

Just as citizens within our own country have access to foreign media, such as BBC and Al Jazeera, foreign citizens have access to ours. Acknowledging this, impression management theory and social desirability bias come into play when explaining why the media is framed the way it is. In his book, The Presentation of Self in Everyday Life, theorist Erving Goffman argued that through impression management, people deliberately and strategically portray themselves in such a manner that creates and manages other’s impressions of themselves in a desirable way (Johansson 2007: 276). An individual will act in a calculated manner, displaying himself in such a way with the purpose of exuding an impression that he aims to obtain (Goffman1959: 6).

Though it may seem that Goffman’s theory strictly applies to communication and interaction between individuals, it has immediate implications for larger organizations and institutions, such as the media, as well (Johansson 2007: 278). As a country viewed as a global superpower, the United States media has the power to act in a calculated manner with the purpose of exuding an impression of economic success to not only its own citizens, but also to others worldwide. Knowing that other key players in the world’s political and economic climate have access to U.S. media, the media is able to solidify the United State’s desirable position and perception of economic power through the use of media framing and impression management. Media consumers across the globe are frequently unsuspicious, and blindly accept the realities portrayed through impression management. This gives the media the opportunity to easily reaffirm their global status, and allows them to gain much by controlling it (Goffman 1959: 8). Though the problems of poverty are far reaching within the United States, just as they are internationally, by rarely covering or depicting domestic poverty, a reality of class stability and equality within the U.S. is conveyed and widely accepted.

Following North America, whose results were skewed because all articles on domestic poverty were on North America, as opposed to the articles on international poverty that were split between regions, the region with the most coverage of poverty was Asia, particularly India. Though no one would argue that poverty is a notable problem in this region, poverty is also a large problem in many other regions, particularly Africa. Interestingly, India and China, countries that both fall within the ‘Asia’ region, are labeled as rising potential superpowers in today’s global society. Just as impression management serves the purpose of framing ones self in a particular light, framing another country in a negative light has the potential to negate that country’s potential for success and power, and may be in place to attempt to undermine their threat to the United State’s current position of power. By avoiding coverage of United States economic downfalls, and more commonly addressing the downfalls of other countries, the media attempts to frame the United States as superior, falsely conveying its success and equality. This rising threat to power may explain why U.S. media most commonly addressed international poverty within the context of Asia.

Considering the implications of agenda setting theory, the under and misrepresentation of domestic poverty, paired with the overall sense of dehumanization, will lead to apathy about the issue within the United States. Consequently, inadequate and insufficient political policy geared towards addressing the problem will emerge. Comparatively however, international poverty was more frequently reported on, and the images accompanying it more commonly depicted the impoverished themselves. This difference lends itself to the more common acceptance and acknowledgement of international poverty, and therefore, an increase in foreign aid and policy.

Due to the nature of this research, time constraints did not allow for a more longitudinal method of data collection. In future research, this study could be improved by coding articles over a longer period of time, perhaps ten years as opposed to one. This would likely eliminate some misrepresentations as a result of over-reporting within certain regions due to significant current events such as historical political uprisings or natural disasters. Noting the potential for the presence of political leanings associated with the reporters of a particular news organization, coding articles from other news magazines, such as Newsweek, rather than solely Time, would help eliminate these biases.

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References

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Appendix

Location_R Frequency Table (Table 1)

Location_R Location Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Domestic	21	26.9	26.9	26.9
	1 International	57	73.1	73.1	100.0
	Total	78	100.0	100.0

Region_R Frequency Table (Table 2)

Region_R Region Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 North America	22	28.2	28.6	28.6
	1 Asia	20	25.6	26.0	54.5
	2 Africa	11	14.1	14.3	68.8
	3 Middle East	11	14.1	14.3	83.1
	4 Caribbean	3	3.8	3.9	87.0
	5 South America	2	2.6	2.6	89.6
	6 Europe	8	10.3	10.4	100.0
	Total	77	98.7	100.0
Missing	System	1	1.3
Total		78	100.0

ImagePresent Frequency Table (Table 3)

ImagePresent CaptionYN_R
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Image Present	76	97.4	98.7	98.7
	1 No Image Present	1	1.3	1.3	100.0
	Total	77	98.7	100.0
Missing	System	1	1.3
Total		78	100.0

Setting_R Frequency Table (Table 4)

Setting_R Setting Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Urban	28	35.9	35.9	35.9
	1 Rural	20	25.6	25.6	61.5
	2 Wealthier Indoor	17	21.8	21.8	83.3
	3 Poorer Indoor	3	3.8	3.8	87.2
	4 Other	10	12.8	12.8	100.0
	Total	78	100.0	100.0

PeopleFocus_R Frequency Table (Table 5)

PeopleFocus_R People Focus Recoding
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Yes	62	79.5	80.5	80.5
	1 No	15	19.2	19.5	100.0
	Total	77	98.7	100.0
Missing	System	1	1.3
Total		78	100.0

Ages_R Frequency Table (Table 6)

Ages_R Ages Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 <18	7	9.0	11.5	11.5
	1 18-64	41	52.6	67.2	78.7
	2 >64	2	2.6	3.3	82.0
	3 Multiple Age Groups	11	14.1	18.0	100.0
	Total	61	78.2	100.0
Missing	System	17	21.8
Total		78	100.0

Races_R Frequency Table (Table 7)

Races_R Race Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 White	11	14.1	17.7	17.7
	1 Black	16	20.5	25.8	43.5
	2 Asian	21	26.9	33.9	77.4
	3 Middle Eastern	6	7.7	9.7	87.1
	4 Hispanic	3	3.8	4.8	91.9
	5 Multiple Races Depicted	5	6.4	8.1	100.0
	Total	62	79.5	100.0
Missing	System	16	20.5
Total		78	100.0

Gender_ R Frequency Table (Table 8)

Gender_R Gender Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Male	30	38.5	46.9	46.9
	1 Female	12	15.4	18.8	65.6
	2 Both Male and Female	19	24.4	29.7	95.3
	3 Undeterminable	3	3.8	4.7	100.0
	Total	64	82.1	100.0
Missing	System	14	17.9
Total		78	100.0

TypePerson_R Frequency Table (Table 9)

TypePerson_R Type Person Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Impoverished	36	46.2	56.3	56.3
	1 Politician	14	17.9	21.9	78.1
	2 Aid/Helper	3	3.8	4.7	82.8
	3 Other	11	14.1	17.2	100.0
	Total	64	82.1	100.0
Missing	System	14	17.9
Total		78	100.0

CaptionYN_R Frequency Table (Table 10)

CaptionYN_R CaptionYN Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Yes	65	83.3	85.5	85.5
	1 No	11	14.1	14.5	100.0
	Total	76	97.4	100.0
Missing	System	2	2.6
Total		78	100.0

SpinCaption_R Frequency Table (Table 11)

SpinCaption_R Spin Caption Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Positive Spin	6	7.7	9.1	9.1
	1 Negative Spin	11	14.1	16.7	25.8
	2 No Spin, Neutral	49	62.8	74.2	100.0
	Total	66	84.6	100.0
Missing	System	12	15.4
Total		78	100.0

MainFocusPoverty_R Frequency Table (Table 12)

MainFocusPoverty_R Main Focus Poverty Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Yes	10	12.8	12.8	12.8
	1 No	68	87.2	87.2	100.0
	Total	78	100.0	100.0

CauseListed_R Frequency Table (Table 13)

CauseListed_R Cause Listed Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Yes	24	30.8	31.6	31.6
	1 No	52	66.7	68.4	100.0
	Total	76	97.4	100.0
Missing	System	2	2.6
Total		78	100.0

SolutionGiven_R Frequency Table (Table 14)

SolutionGiven_R Solution Given Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Yes	21	26.9	26.9	26.9
	1 No	57	73.1	73.1	100.0
	Total	78	100.0	100.0

EconGovt_R Frequency Table (Table 15)

EconGovt_R EconGovt Recoded
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	0 Yes	12	15.4	15.4	15.4
	1 No	66	84.6	84.6	100.0
	Total	78	100.0	100.0

Crosstab between EconGovt_R and Location _R (Table 16)

EconGovt_R EconGovt Recoded * Location_R Location Recoded Crosstabulation
			Location_R Location Recoded		Total
			0 Domestic	1 International
EconGovt_R EconGovt Recoded	0 Yes	Count	8	4	12
		% within Location_R Location Recoded	38.1%	7.0%	15.4%
	1 No	Count	13	53	66
		% within Location_R Location Recoded	61.9%	93.0%	84.6%
Total		Count	21	57	78
		% within Location_R Location Recoded	100.0%	100.0%	100.0%

EconGovt_R and Location _R Chi Square Test (Table 17)

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)	Exact Sig. (2-sided)	Exact Sig. (1-sided)
Pearson Chi-Square	11.386a	1	.001
Continuity Correctionb	9.124	1	.003
Likelihood Ratio	10.098	1	.001
Fisher's Exact Test				.002	.002
Linear-by-Linear Association	11.240	1	.001
N of Valid Cases	78
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.23.
b. Computed only for a 2x2 table

Crosstab between PeopleFocus_R and Location_R (Table 18)

PeopleFocus_R People Focus Recoding * Location_R Location Recoded Crosstabulation
			Location_R Location Recoded		Total
			0 Domestic	1 International
PeopleFocus_R People Focus Recoding	0 Yes	Count	13	49	62
		% within Location_R Location Recoded	65.0%	86.0%	80.5%
	1 No	Count	7	8	15
		% within Location_R Location Recoded	35.0%	14.0%	19.5%
Total		Count	20	57	77
		% within Location_R Location Recoded	100.0%	100.0%	100.0%

PeopleFocus_R and Location_R Chi Square Test (Table 19)

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)	Exact Sig. (2-sided)	Exact Sig. (1-sided)
Pearson Chi-Square	4.149a	1	.042
Continuity Correctionb	2.920	1	.088
Likelihood Ratio	3.804	1	.051
Fisher's Exact Test				.054	.048
Linear-by-Linear Association	4.095	1	.043
N of Valid Cases	77
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.90.
b. Computed only for a 2x2 table

Crosstab between Setting_R and Location_R (Table 20)

Setting_R Setting Recoded * Location_R Location Recoded Crosstabulation
			Location_R Location Recoded		Total
			0 Domestic	1 International
Setting_R Setting Recoded	0 Urban	Count	6	22	28
		% within Location_R Location Recoded	28.6%	38.6%	35.9%
	1 Rural	Count	1	19	20
		% within Location_R Location Recoded	4.8%	33.3%	25.6%
	2 Wealthier Indoor	Count	6	11	17
		% within Location_R Location Recoded	28.6%	19.3%	21.8%
	3 Poorer Indoor	Count	0	3	3
		% within Location_R Location Recoded	.0%	5.3%	3.8%
	4 Other	Count	8	2	10
		% within Location_R Location Recoded	38.1%	3.5%	12.8%
Total		Count	21	57	78
		% within Location_R Location Recoded	100.0%	100.0%	100.0%

Setting_R and Location_R Chi Square Test (Table 21)

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	21.345a	4	.000
Likelihood Ratio	21.749	4	.000
Linear-by-Linear Association	10.766	1	.001
N of Valid Cases	78
a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is .81.

Crosstab between SolutionGiven_R and Location_R (Table 22)

SolutionGiven_R Solution Given Recoded * Location_R Location Recoded Crosstabulation
			Location_R Location Recoded		Total
			0 Domestic	1 International
SolutionGiven_R Solution Given Recoded	0 Yes	Count	6	15	21
		% within Location_R Location Recoded	28.6%	26.3%	26.9%
	1 No	Count	15	42	57
		% within Location_R Location Recoded	71.4%	73.7%	73.1%
Total		Count	21	57	78
		% within Location_R Location Recoded	100.0%	100.0%	100.0%

Crosstab Between TypePerson_R and Location_R (Table 23)

TypePerson_R Type Person Recoded * Location_R Location Recoded Crosstabulation
			Location_R Location Recoded		Total
			0 Domestic	1 International
TypePerson_R Type Person Recoded	0 Impoverished	Count	4	32	36
		% within Location_R Location Recoded	28.6%	64.0%	56.3%
	1 Politician	Count	4	10	14
		% within Location_R Location Recoded	28.6%	20.0%	21.9%
	2 Aid/Helper	Count	1	2	3
		% within Location_R Location Recoded	7.1%	4.0%	4.7%
	3 Other	Count	5	6	11
		% within Location_R Location Recoded	35.7%	12.0%	17.2%
Total		Count	14	50	64
		% within Location_R Location Recoded	100.0%	100.0%	100.0%

TypePerson_R and Location_R Chi Square Test (Table 24)

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	6.617a	3	.085
Likelihood Ratio	6.396	3	.094
Linear-by-Linear Association	6.283	1	.012
N of Valid Cases	64
a. 4 cells (50.0%) have expected count less than 5. The minimum expected count is .66.

Crosstab between Class_R and Location_R (Table 25)

Class_R Class Recoded * Location_R Location Recoded Crosstabulation
			Location_R Location Recoded		Total
			0 Domestic	1 International
Class_R Class Recoded	0 Lower Class	Count	3	30	33
		% within Location_R Location Recoded	23.1%	60.0%	52.4%
	1 Upper Class	Count	7	14	21
		% within Location_R Location Recoded	53.8%	28.0%	33.3%
	2 Undeterminable	Count	3	6	9
		% within Location_R Location Recoded	23.1%	12.0%	14.3%
Total		Count	13	50	63
		% within Location_R Location Recoded	100.0%	100.0%	100.0%

Class_R and Location_R Chi Square Test (Table 26)

Chi-Square Tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	5.639a	2	.060
Likelihood Ratio	5.847	2	.054
Linear-by-Linear Association	4.486	1	.034
N of Valid Cases	63
a. 2 cells (33.3%) have expected count less than 5. The minimum expected count is 1.86.

Race_R, Location_R and TypePerson_R Layered Crosstab (Table 27)

Race_R Race Recoded * Location_R Location Recoded * TypePerson_R Type Person Recoded Crosstabulation
TypePerson_R Type Person Recoded				Location_R Location Recoded		Total
				0 Domestic	1 International
0 Impoverished	Race_R Race Recoded	1 Black	Count	3	8	11
			% within Location_R Location Recoded	75.0%	28.6%	34.4%
		2 Asian	Count	0	18	18
			% within Location_R Location Recoded	.0%	64.3%	56.3%
		4 Hispanic	Count	0	1	1
			% within Location_R Location Recoded	.0%	3.6%	3.1%
		5 Multiple Races Represented	Count	1	1	2
			% within Location_R Location Recoded	25.0%	3.6%	6.3%
	Total		Count	4	28	32
			% within Location_R Location Recoded	100.0%	100.0%	100.0%
1 Politician	Race_R Race Recoded	0 White	Count	3	3	6
			% within Location_R Location Recoded	75.0%	30.0%	42.9%
		1 Black	Count	1	4	5
			% within Location_R Location Recoded	25.0%	40.0%	35.7%
		4 Hispanic	Count	0	2	2
			% within Location_R Location Recoded	.0%	20.0%	14.3%
		5 Multiple Races Represented	Count	0	1	1
			% within Location_R Location Recoded	.0%	10.0%	7.1%
	Total		Count	4	10	14
			% within Location_R Location Recoded	100.0%	100.0%	100.0%
2 Aid/Helper	Race_R Race Recoded	0 White	Count	1	1	2
			% within Location_R Location Recoded	100.0%	50.0%	66.7%
		2 Asian	Count	0	1	1
			% within Location_R Location Recoded	.0%	50.0%	33.3%
	Total		Count	1	2	3
			% within Location_R Location Recoded	100.0%	100.0%	100.0%
3 Other	Race_R Race Recoded	0 White	Count	1	2	3
			% within Location_R Location Recoded	20.0%	50.0%	33.3%
		2 Asian	Count	0	2	2
			% within Location_R Location Recoded	.0%	50.0%	22.2%
		5 Multiple Races Represented	Count	2	0	2
			% within Location_R Location Recoded	40.0%	.0%	22.2%
		6 Other	Count	2	0	2
			% within Location_R Location Recoded	40.0%	.0%	22.2%
	Total		Count	5	4	9
			% within Location_R Location Recoded	100.0%	100.0%	100.0%