QUANTITATIVE DATA SOURCES

Through a large-n application of my research project, I seek to explain variation in intimate partner femicide in Latin American and European states with the highest femicide rates. This allows me to examine 33 countries: 14 in Latin America and 19 in Europe. My dependent variable is the number of intimate partner femicides in each state per 100,000 women.

Femicide data is limited by the various time frames in which data has been collected. Few datasets measure femicide from 2004-2009 while others report femicide by individual years. Furthermore, limitations to data collection include a universal understanding of a lack of collected data. [1] Reasons for this insufficiency are enumerated as follows:

  1. many femicides go unreported
  2. when reported, femicides are often measured indiscriminately in regards to general homicide
  3. many states do not invest in collecting femicide data

Despite a general lack of data, a variety of platforms have measured the highest rates of femicide by region. States with the highest femicide rates from 2004-2009 are comprehensively quantified by the Small Arms Survey. [2]  This data collection measures the number of women killed by an intimate partner of the 25 states with the overall highest rates of femicide worldwide. [3] Of these 25 states, 14 are from Latin America, according to data from the Geneva Declaration. [4] The Economic Commission for Latin America and the Caribbean measures intimate partner femicide from every state within the region between 2001 and 2017. [5] To measure femicide statistics in Europe, the Osservatorio Balcani e Caucaso lists victims of femicide from Europe’s 19 states with the highest femicide rates. [6]

All datasets demonstrate states’ overall femicide rates in comparison to the rate of femicide due to intimate partner violence. Datasets also all measure the ratio in terms of  a female population of 100,000.

NOTES

[1] “Femicide” Understanding and Addressing Violence against Women. World Health Organization. 2012. http://apps.who.int/iris/bitstream/handle/10665/77421/WHO_RHR_12.38_eng.pdf;jsessionid=94F058F451AB565AD8E881E78BE0CB87?sequence=1.

[2] Femicide:  A Global Problem. Armed Violence. Small Arms Survey. February 2012. http://www.smallarmssurvey.org/fileadmin/docs/H-Research_Notes/SAS-Research-Note-14.pdf.

[3] “When the Victim Is a Woman.” Geneva Declaration. Global Burden of Armed Violence. Chapter 4, pp. 129. 2011. http://www.genevadeclaration.org/fileadmin/docs/GBAV2/GBAV2011_CH4.pdf

[4] Ibid. 119.

[5] “CEPALSTAT Indicador 1345.” Accessed October 8, 2018. http://interwp.cepal.org/sisgen/ConsultaIntegrada.asp?idIndicador=1345&idioma=e.

[6] Caucaso, Osservatorio Balcani e. “Femicide: the numbers in Europe.” Osservatorio Balcani e Caucaso. November 28, 2017. https://www.balcanicaucaso.org/eng/Areas/Europe/Femicide-the-numbers-in-Europe-184329.

[7] Ibid.

[8] Ibid.

BIBLIOGRAPHY

Caucaso, Osservatorio Balcani e. “Femicide: the numbers in Europe.” Osservatorio Balcani e Caucaso. November 28, 2017. https://www.balcanicaucaso.org/eng/Areas/Europe/Femicide-the-numbers-in-Europe-184329.

“CEPALSTAT Indicador 1345.” Accessed October 8, 2018. http://interwp.cepal.org/sisgen/ConsultaIntegrada.asp?idIndicador=1345&idioma=e.

Femicide: A Global Problem. Armed Violence. Small Arms Survey. February 2012. http://www.smallarmssurvey.org/fileadmin/docs/H-Research_Notes/SAS-Research-Note-14.pdf.

“Femicide” Understanding and Addressing Violence against Women. World Health Organization. 2012. http://apps.who.int/iris/bitstream/handle/10665/77421/WHO_RHR_12.38_eng.pdf;jsessionid=94F058F451AB565AD8E881E78BE0CB87?sequence=1.

“When the Victim Is a Woman.” Geneva Declaration. Global Burden of Armed Violence. Chapter 4, pp. 129. 2011. http://www.genevadeclaration.org/fileadmin/docs/GBAV2/GBAV2011_CH4.pdf

One Comment

  1. Reply
    Dr. Boesenecker October 18, 2018

    Theodora — the overall conceptualization of your DV looks good, and you’ve done a good job in finding some data sources that would help you in assembling a dataset should you choose to pursue this variant of the project. My only question though is why limit the scope of the potential analysis by region? As we’ve discussed, more data coverage is better in terms of (1) eliminating inbuilt statistical bias, and (2) increasing the analytical leverage of any statistical analysis. The way to assess for differences in regions would be to include control variables, not to limit the data just to certain regions (though there may be limitations for other reasons, such as data availability).

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