This page presents additional analysis of survey data collected by the Argentinian Red Cross (ARCS) in early 2023, covering questions around trust as part of the Community Trust Index project.

Sampling

The sampling employed a convenient sampling approach focused on large parts of the country in Argentina. The coverage overall is 96% of the country, when looking at inhabitants at the province level.

Coverage

According to the provided information, the survey was mainly conducted at ARCS-organised events, which can be seen in the GPS coordinates (rounded to one digit of longitude and latitude), which indicate many local clusters and and focus mainly on cities.

Overall, such sampling approach ensures familiarity with the ARCS, but also comes with the danger of biasing results, in particular social-desirability bias.

It is important to note that this non-probability design does not allow for inferences to be made about the general population in Argentina. Therefore, all the data should be regarded as indicative, and it is strongly advised against presenting this data as representative of the entire country of Argentina, as the convenience sampling approach taken does not allow for drawing generalizations for the population in Argentina.

However, a post-stratification technique can be employed to ensure that the weighted sample corresponds to some features of the population more closely. Therefore, a initial analysis focuses on a few demographic parameters of our sample and compares them to the overall population in the country.

Except for seven of the 23 provinces, all the provinces of Argentina were covered in the sample. Since the seven that were not included are not highly populated, 96% of the Argentinian population lived in the surveyed provinces in 2022, which is a very high coverage in the context of the Community Trust Index project. Besides some deviations, the sample was roughly allocated proportionally the population of the respective province.

Gender and age group

For the following demographic data, we show the full data set including people who indicated to volunteered for the ARCS as well as those who benefited from the ARCS.

Demographic Total Female Male Other response
Respondents 3017 1678 1247 92

Compared to the overall Argentinean population, in the sample women, especially younger women are over-represented, while elderly people are under-represented.

Education

While we have not managed to access to demographic data on education using the same levels as the survey, the survey demographics on education at first glance seems to correspond to expected values of the various levels of education in the overall population, with the exception of percentages of complete and uncompleted university degrees.

As we will see in the employment questions, full time students with approximately 10% are over-represented in the survey population, which in the overall Argentinian population above 18 was close to 6% in 2020. Our weighting procedure will correct this large share of students when calculating the weighted overall results.

Employment

The sample’s demographic composition on employments status seems to indicate that people interviewed have a much higher rate of unemployment than the average of the country, which had an unemployment rate of 6.5% in 2022 and labor force participation rate of 60% in the same year.

Relationship with Red Cross

Overall, the numbers of people in the sample who benefited from the ARCS as well as those who volunteered are high compared to expected values of the general population. However, the sample focused on ARCS run-events and thus higher percentages of volunteering and having received support are be expected.

Results

Scores distribution

Distribution of mean scores for values and competencies per demographic questions

To calculate the score, we divide the sum of all responses by the number of responses using a response scale ranging from 0 (Not at all) to 3 (Completely yes). Finally, the score is normalized on a scale of 0 to 10, where 0 represents the lowest score and 10 represents the highest score.

The raw scores (without weighting) for the socio-demographic factors and for the “Competencies” and “Values” variables are presented below.

Upon analyzing the data, we observe that there are not significant variations in the results based on age, gender, previous beneficiary status or volunteer status. The largest variations we see for the location variable. The province where the survey was conducted plays the largest role in contributing to the variation of the results. However, since the sample allocation per province was done almost proportionally, we do not expect large changes once the weighting has been implemented.

Weighting

To address the deviation of demographic parameters from the overall population, we have utilized a technique called raking. The raking process adjusts the results based on several variables to ensure that our sample reflects the distribution of these variables in the overall population. Here are the variables we considered for raking:

  • Age groups and gender: We used UN data to determine the proportions of different age groups and gender in the population.
  • Provinces: We used 2022 on population per province from the National Institute of Statistics and Censuses
  • Students: we used 2020 data on student population from the National Institute of Statistics and Censuses

Using an appropriate package in R to conduct the raking, we obtained the following results.

While the weighted results have slightly smaller means, on difference only to a minor extend form the un-weighted data, except for the question on openness, where we see a slighlty bigger decrease in the overall mean value.

Weighted Results

Here we are presenting the weighted data obtained through the raking process, which takes into account the variables gender, age groups, province, and full-time student status. It is important to note that this data can be biased due to sampling done at ARCS-organised events in urban areas. Hence it should be considered indicative rather than representative of the entire country. The results on all the competency and value questions range between 7.99 and 9.15 on the 0-10 scale, except the questions on openness (6.26) and transparency (5.66). This particular low ratings on this questions might warrant further investigation on why survey respondents rank the ARCS lower on these topics.

Results per participants

When looking at the sub-groups of people who volunteered and beneficiaries as well as others, we see that people who have received support from the ARCS provide the most positive rating from the three groups. For all questions besides relevance and openness, beneficiaries’ perceptions of the ARCS are the highest compared to the other two groups (the question on relevance and openness were answered slightly higher by volunteers).

The non-volunteer/beneficiary group, on the other hand provides the lowest ranking among the three groups, except for the question on transparency, where we see volunteers actually having the lowest rating (by a small margin of 0.12 on the 0-10 scale). However, this difference is with the sample size at hand not significant.

Download Summary Excel File