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Enumerator Experiences in Violent Research Environments

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Martha Wilfahrt and Justine Davis discuss how survey enumerators in violent research settings face unique security concerns that affect data collection. Personal insecurity and exposure to violence influence their challenges and compromises.

Image courtesy of interviewee. December 14, 2023

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This video video discusses the rise in academic surveys and field experiments conducted in the Global South, emphasizing the important role of survey enumerators in the process. These enumerators, who often have a university education, typically work as gig workers, contributing their skills to collect data for various research projects. They take pride in their work, valuing the professional development and opportunities for learning about their countries.

The authors highlight a lack of understanding regarding the experiences and working conditions of enumerators, especially in insecure contexts marked by violence or conflict. Risks faced by enumerators can impact data quality due to reported instances of violence, threats, and specific challenges in engaging with respondents. This video video study aims to shed light on this issue and emphasize the ethical considerations of placing enumerators in potentially dangerous situations.

Significant findings include the high percentage of enumerators feeling unsafe or fearing for their physical safety while conducting interviews. The study reveals challenges encountered, including violent encounters and difficulties ensuring respondents' cooperation. The authors advocate for better engagement with enumerators in the research design process, including considerations for their safety and mental health, as well as adapting survey questions to local contexts.

Lastly, the paper offers several recommendations for researchers to improve enumerator welfare and enhance data validity, such as establishing disciplinary norms for research in insecure areas, adapting research designs to minimize enumerator risk, and collecting feedback on enumerator experiences before and after data collection. By addressing these issues, the authors hope to foster a more ethical and effective research environment.

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Here are some key quotes drawn from the video you :

1. **Growing Research in the Global South**:
- "The past decade or two has seen a sharp uptick in the number of academic surveys and field experiments being conducted in the global south."

2. **The Role of Survey Enumerators**:
- "These survey enumerators... are very proud of the work that they do."
- "They report really valuing the professional skills that they can develop in the course of doing academic research."

3. **Navigating Insecure Convideos**:
- "We don’t actually know a lot about the research experience... of these people who are doing a large number of surveys every day."
- "We think that these concerns would be particularly acute because we're just further from the data collection process."

4. **Survey Enumerator Challenges**:
- "Almost 60% of the enumerators in our study felt unsafe, at least sometimes while conducting academic surveys."
- "Over 75% reported fearing for their physical safety."

5. **Experience of Violence**:
- "About a third had been followed," and "26% had been threatened with physical violence."
- "Enumerators also witnessed violence while on the job, including violent protests, threats, harassment and physical violence."

6. **Impact on Data Quality**:
- "When enumerators face insecurity, they're more likely to overcome challenges by adapting or breaking survey protocols."
- "These breaches hold potentially serious consequences for the quality of the data we collect."

7. **Recommendations for Improvement**:
- "We urge researchers to continue efforts towards establishing disciplinary norms around research in insecure settings."
- "Understanding the working conditions can help alleviate some of these risks."

8. **Emphasis on Collaboration**:
- "Including enumerators in all aspects of the research design to make sure that we're asking culturally sensitive questions that are adapted to local realities."

These quotes encapsulate the primary themes of the video, highlighting the experiences of survey enumerators in insecure convideos and the implications for both ethical considerations and data quality in research.

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

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So the past decade or two has seen a sharp uptick in the

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number of academic surveys

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and field experiments being conducted in the global south.

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And one consequence of this,

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or perhaps a driver of it, is that there's a growing number

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of firms, many of which are very high quality,

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that are available to do this kind

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of research for researchers.

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So based on our data, or sorry,

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and I should say, so those firms then need to hire people

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to go out in the field and, you know,

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collect our surveys.

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And so those are survey enumerators.

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So based on our data, and anecdotally from other research

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that Jesse and I have both done in West Africa,

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these survey animators are generally,

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you know, pretty well educated.

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They're often completing university or finished university,

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and they're essentially doing gig work,

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which means they might take a contract

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to run an academic survey one week,

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and then a few weeks later they work on the national

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census or something like this.

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Um, and so we wanna stress at the outset

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that these survey enumerators,

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are very proud of the work that they do.

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And so in both close and open-ended questions,

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they report really valuing the professional skills

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that they can develop in the course

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of doing academic research.

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They like to be able to travel

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and learn about their countries, which

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otherwise might not always be options for a lot

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of these people that like participate in the research

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process and they hope that they can help in some way.

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They're co citizens in the process

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of doing academic research.

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So these are people who are hired to do their job

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and are trying to do the best of their, ability.

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But what we've realized in sort

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of thinking about our own research experiences is

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that we don't actually know a lot about the research,

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you know, experience or sort of their actual sort

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of work experience of these people

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who are doing a large number of surveys every day

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for weeks on end to sort of, you know, produce data

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that arrives to us in our inboxes.

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And so we really wanted to think about this in particular,

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in the case of insecure context, by which we mean countries

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that might have an ongoing conflict.

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There's a growing discussion about research ethics in

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violent context, in political science

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and adjacent disciplines, but also

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because we think that this might impact the data

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that we receive in ways that we would wanna understand

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as researchers if there's systematic sources

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of biases in one way or the other.

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So to the extent that research enumerators

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or survey enumerators go out into communities, they have

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to knock on doors, they have to attempt to sort

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of get respondents to agree to participate.

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They have to walk them through very lengthy

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and very legalistic consent forms that might be very foreign

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to a lot of, you know, perhaps not particular, you know,

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people without high literacy skills.

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They have to sit with those people for some length

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of time asking them

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what sometimes are pretty sensitive questions.

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Um, to that extent, we think

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that these numerator are engaged in really important acts

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of brokerage on our behalf as researchers.

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So there's been some sustained attention

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to thinking about research assistance as brokers.

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It's largely been done by anthropologists

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or demographers people who tend to spend a fair amount

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of time in the field and tend to work with one

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or a small number of brokers.

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And this work has tended to emphasize sort

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of the unequal relationship between researchers

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and research brokers.

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Um, and that these are, you know,

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this work is also really thought about the ways in which,

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how that in inequity is acute in conflict settings,

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where brokers not only are providing us with data,

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but often are helping sort

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of navigate security concerns like

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roadblocks for researchers.

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So given this uptick in remote research

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and the ease with which we can now do, you know,

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big surveys in the field, well, you know, you know,

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researchers often based in the global north sit at

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home, you know, in our offices.

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Um, we thought sort of, we wanna sort of suggest that sort

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of, we bring some of these insights from this work on

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research brokerage from adjacent disciplines to think about

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what the implications are for survey research.

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And we think that these concerns would be particularly acute

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because we're just further from the data collection process

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when we work with a firm

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or sort of employ a large number of survey enumerators,

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even if we hire those enumerators ourselves.

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And so when we have a survey, there's just more people,

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it tends to be more decentralized.

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And so you have a bunch of enumerators working under a team

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leader working, you know, hired by a firm.

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And we might be able to communicate with the firm, maybe

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with the team leader, but we don't necessarily know

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what information is being filtered up to us.

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And so we wanted to understand sort of, if we talk

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to enumerators themselves, right,

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what are their working conditions?

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They are really important to the research effort.

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But often in things like IRB,

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we aren't asked questions about how we're going

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to protect their security,

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or ensure that they themselves don't face, you know,

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dangerous context, despite the fact

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that they are the ones on the ground

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collecting the data for us.

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Um, and so what that was another motivation

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for pursuing this is that we often just kind of think

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of them as neutral actors

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that are just out there doing this work for us.

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Um, but in reality they have

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to navigate these contexts just like the respondents

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that are answering our surveys,

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do in in insecure settings

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that can include violence witnessing violent violence,

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experiencing violence themselves.

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We certainly have paid attention to survey enumerators

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before, but the vast majority

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of work is focused on sort of two things.

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So first we know a growing amount about the enumerator

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respondent dyad.

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So most work here has focused on how characteristics

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of the enumerators might elicit certain types

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of responses by respondents.

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So there's been work by CLA data

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and a number of co-authors on how ethnicity a respondent

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or co enumerators ethnicity might cue certain types

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of respondents from either co-ethnic

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or non co-ethnic survey respondents.

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There's been work on gender, there's been work on sort

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of religious dress by Lindsay Bedstead and others.

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Um, and it's all been shown to influence sort of

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how an enumerator,

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something about the enumerators characteristics are shaping

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the responses they get from respondents.

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Secondly, there's been some work

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that I think is encapsulated well in a,

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piece in the annual review of political science by no Lupa

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and Kristen Michel that sort of has thought about

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how enumerators own behavior might

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shape the data generating process.

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And in particular about concerns over, fabricated data.

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But there's also been work that's just thought about

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how enumerators might accelerate surveys.

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They might develop priors that are gonna influence

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how they approach certain questions, et cetera.

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And so the biggest concern here, of course, is really about

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how enumerators themselves are doing something

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to impact data quality.

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Um, so both of these literatures have distinct implications.

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So if it's the former, if we think it's something about

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enumerator characteristics that are influencing responses,

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then something like including enumerator fixed effects

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or a dummy variable for an enumerator agenda in our,

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you know, models that we might run could maybe address that

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if we think it's something about that enumerators are doing,

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like, perhaps more related

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to like their professionalism, let's say.

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Right? Then, you know, there's also techniques.

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So increasingly surveys are run on tablets,

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and so we might be able to sort of see

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how long a survey took, right?

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And a survey didn't take long enough.

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We might have questions about the quality of the survey,

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or sometimes we can geolocate that so we know whether

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or not a survey enumerator is actually going

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to different households or just sitting in one spot filling

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out surveys at the end of the day.

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Um, and of course we can also think about other techniques

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to sort of, you know, design questions

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that are particularly clever to maybe address some

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of these concerns, et cetera.

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So that literature all exists and we think it's important,

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but we don't think it's actually capturing sort

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of the political context that sort

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of enumerators are working in, which we think is sort

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of a distinct driver of,

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both enumerator work experiences that we care about

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for normative reasons, but also data quality reasons

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that we'll talk about more in a few minutes.

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But we thought about, our own experiences

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and I've, I've had a lot of experience working in TiVo,

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with Enumerators there.

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And so what we did, is we recruited a diverse set

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of roughly 300,

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enumerators from the top three research firms in co dvo.

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Um, the reason that co dvo is actually really interesting,

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is several fold.

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So first, it is a site of,

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surveys and academic research.

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Um, there's a number of publications, that have,

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included data from TiVo.

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Um, the Afro Barometer has been conducted there several

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rounds, but crucially, the political context is

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what we are particularly interested in.

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Um, and TiVo unfortunately,

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experienced the civil war from 2002 to 2011,

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and has experienced a, a high level of,

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election related violence, ethnic violence.

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Um, and so we see a high level of insecurity,

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for people living in the country as well as enumerators

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who are conducting this research.

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Um, and so the goal that we had then was to get,

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an understanding of these enumerator experiences.

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So we recruited them from these top three firms.

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Um, they ultimately represented all

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of the ethnic groups in co TiVo,

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and had substantial experience in the sector.

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Um, as Martha said, these folks tend

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to be more educated than the general population,

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and to have like master's degrees and that sort,

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and they tend to come from more urban settings,

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although, one

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of the nice things about our recruitment strategy is

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that some of these survey firms like to recruit locally,

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and so many of the enumerators,

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come from sometimes even rural villages.

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Um, and so what we asked them to do was

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to complete an online survey about the sum

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of their enumerator experiences.

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Um, we asked them about, just general, you know,

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where have you worked, what did you do,

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the challenges they faced while implementing projects,

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the challenges they encountered as a function

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of the survey content,

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and then solutions they may have employed when they

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ran into these challenges.

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We also included several open-ended questions

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because we really wanted to gather, stories of how,

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they experienced challenges,

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but also how they navigated them.

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So one of the limitations of this data, just to kind

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of start there, is that it's collected

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at the enumerator level.

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We were particularly interested in the sum

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of their experiences because first, descriptively,

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this hasn't really been investigated.

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We don't know how often,

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enumerators encounter challenges in these settings.

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We wanted to actually get kind of a baseline for that.

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Um, but the limitation about that is

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that we don't know if a specific project

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or specific survey led to more challenges

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or fewer challenges.

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Um, so that's one particular limitation.

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And we think that future research certainly,

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and we, we have a lengthy implication section in the paper,

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but future research researchers should consider asking

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these questions at the end of every project

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and potentially even at the beginning to find out

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what has been the experiences of the enumerators

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that you're employing on your project.

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Um, so nonetheless, we wanted to know the sum

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of their experiences to understand the scope

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and the magnitude

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of the challenges they face when

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conducting this type of research.

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Um, and again, I also wanna reiterate

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that this project is primarily descriptive.

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Um, we wanted to detail the challenges

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that enumerators faced,

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because they're often overlooked,

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but extremely important actor in our research endeavor.

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Um, so that's kind of covering the, the data

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and, why we selected co vo.

10:32.345 --> 10:34.485
One other note that I'll say about co vo,

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people often are like, it's a small country.

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Um, you know, what can that tell us about Africa?

10:39.385 --> 10:43.645
Um, but in reality, co vo can represent a case of,

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high levels of insecurity, a lot

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of polarization on both ethnic

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and political lines, which could definitely generalize

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to places like Molly Burkina Faso,

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Madagascar, South Africa.

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And in the paper we also include,

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some data from the ARO Barometer to show

11:01.925 --> 11:04.005
that people across the continent,

11:04.005 --> 11:05.725
enumerators across the continent,

11:06.025 --> 11:08.605
are experiencing insecurity when they conduct this research.

11:08.825 --> 11:10.205
And this is something that we often

11:10.215 --> 11:11.525
don't think about or consider.

11:11.985 --> 11:13.765
Um, and this is happening everywhere.

11:13.865 --> 11:17.165
So though Covar is a small case, we think it kind

11:17.165 --> 11:19.125
of represents and is a good launching

11:19.125 --> 11:20.245
pad for this research agenda.

11:20.865 --> 11:24.005
But we do, in the paper though, is show relationships

11:24.035 --> 11:25.125
between,

11:25.125 --> 11:27.285
and I'm, I can start talking about, the,

11:27.345 --> 11:28.525
the findings in particular.

11:28.945 --> 11:31.965
Um, but we show relationships between experiences

11:32.065 --> 11:34.565
of violence or witnessing violence,

11:34.705 --> 11:37.205
and higher likelihood of facing these challenges.

11:37.585 --> 11:40.885
Um, and while we can't say, you know, enumerator x

11:41.835 --> 11:45.245
experienced violence and then also had this challenge in the

11:45.245 --> 11:46.965
same survey, and that's one of the limitations

11:46.965 --> 11:50.165
with the data, what we can say is that,

11:50.795 --> 11:52.805
unfortunately we document

11:52.835 --> 11:55.645
that these enumerators are experiencing high levels

11:55.665 --> 11:57.245
of violence, witnessing violence,

11:57.825 --> 11:59.685
and are facing a number

11:59.685 --> 12:02.285
of challenges when they're conducting our research in ways

12:02.285 --> 12:04.845
that often as researchers we don't consider

12:04.865 --> 12:06.045
or hadn't even thought about.

12:06.385 --> 12:08.085
Um, I was kind of queued to this,

12:08.105 --> 12:09.205
and it kind of was the reason

12:09.205 --> 12:13.005
that we started this project when I did a project in Cote Vo

12:13.005 --> 12:14.285
about, election violence.

12:14.705 --> 12:17.405
And the enumerators were sending me WhatsApp messages like,

12:17.745 --> 12:19.325
we're being followed when we

12:19.325 --> 12:20.365
were trying to conduct this survey.

12:20.505 --> 12:22.685
And so that kind of made me think,

12:22.945 --> 12:24.285
how often does this actually happen?

12:24.345 --> 12:26.085
And so that's the, the point of the paper.

12:26.545 --> 12:29.045
Um, we don't see it, we see it kind of

12:29.045 --> 12:31.485
as opening a research agenda as opposed to kind

12:31.485 --> 12:33.045
of having a final word on this topic.

12:33.465 --> 12:35.805
One of the most concerning result that we had was

12:35.805 --> 12:40.005
that almost 60% of the enumerators in our study felt unsafe,

12:40.225 --> 12:42.605
at least sometimes while conducting academic surveys,

12:42.775 --> 12:46.285
while over 75% reported fearing for their physical safety.

12:46.865 --> 12:48.165
And this is enormous.

12:48.745 --> 12:50.805
Um, this means that these are folks

12:50.905 --> 12:54.325
who every day in their work potentially are feeling this

12:54.325 --> 12:56.765
way, feeling unsafe, feeling, threatened.

12:57.265 --> 13:00.605
Um, three quarters of enumerated surveyed reported fearing

13:00.605 --> 13:02.005
for their personal physical safety.

13:02.625 --> 13:05.285
Um, 50% felt unsafe.

13:06.185 --> 13:08.685
Um, and what does this kind of, these threats

13:08.745 --> 13:09.765
or violence look like?

13:10.345 --> 13:12.805
Um, so about a third had been followed.

13:13.585 --> 13:16.925
Um, 26% had been threatened with physical violence.

13:17.105 --> 13:19.045
And to just give you an example,

13:19.045 --> 13:21.765
an enumerator told us in the open-ended question,

13:22.025 --> 13:24.925
during the war when, when they were conducting a survey

13:24.955 --> 13:28.085
that rebels were everywhere, they were following us,

13:28.205 --> 13:30.445
a respondent told us that since we had been

13:31.005 --> 13:32.005
identified we were being followed.

13:32.385 --> 13:33.965
And so this is something that came up

13:34.215 --> 13:35.605
often in, in the survey.

13:36.505 --> 13:38.365
Um, in addition to experiencing violence,

13:38.435 --> 13:40.685
enumerators also witnessed violence while on the job,

13:40.875 --> 13:43.725
including violent protests, threats, harassment

13:43.905 --> 13:44.925
and physical violence.

13:45.825 --> 13:48.205
So in addition to experiencing this violence

13:48.345 --> 13:50.365
and witnessing it, but they face a number of,

13:50.465 --> 13:51.885
challenges in the field.

13:52.195 --> 13:54.165
They feel unsafe due the con due

13:54.165 --> 13:55.485
to the conditions in which they work,

13:55.485 --> 13:57.605
including the polarized political environment,

13:57.675 --> 14:00.285
high crime rates and isolation of the field sites, feeling

14:00.285 --> 14:02.485
that they wouldn't be able to escape if they

14:02.725 --> 14:03.805
were encountered with violence.

14:04.665 --> 14:07.205
Um, they reported that the respondents

14:07.265 --> 14:10.485
and their families were the most difficult for them,

14:10.485 --> 14:13.605
sometimes even an extreme that families would threaten them

14:13.605 --> 14:14.645
with physical aggression

14:14.705 --> 14:17.365
or even keep them, hostage in their homes.

14:17.945 --> 14:19.285
Um, verbal threats

14:19.305 --> 14:22.005
and harassment increase the sense of discomfort

14:22.025 --> 14:23.565
and fear that these eners have.

14:24.505 --> 14:26.965
So what we show is that experiencing violence

14:27.185 --> 14:31.685
and working in difficult in a context, are more likely

14:31.865 --> 14:34.965
to talk about how, they have this,

14:34.965 --> 14:36.645
that it's psychologically challenging for them

14:36.645 --> 14:38.325
to do this work,

14:38.745 --> 14:41.325
and that they faced more challenges from,

14:41.475 --> 14:42.965
from the local population.

14:43.705 --> 14:45.045
So that's first the ethical

14:45.185 --> 14:47.085
and normative concern that we have, right?

14:47.585 --> 14:51.405
Um, that perhaps when we ask them to do, do this work

14:51.405 --> 14:53.285
for us, we're putting them both in physical

14:53.345 --> 14:54.485
and psychological danger,

14:55.305 --> 14:57.645
but we also show that there's serious ramifications

14:57.645 --> 14:58.725
for data validity.

14:58.955 --> 15:01.445
When enumerators face insecurity, they're more likely

15:01.465 --> 15:03.365
to overcome challenges by adapting

15:03.505 --> 15:05.045
or breaking survey protocols.

15:05.305 --> 15:08.005
And these breaches hold potentially serious consequences

15:08.105 --> 15:10.045
for the quality of the data we collect.

15:10.545 --> 15:13.405
And even if it seems benign, like skipping a household,

15:13.545 --> 15:16.285
for example, or deviating from a random walk protocol

15:16.305 --> 15:17.685
to avoid dangerous neighborhoods,

15:18.035 --> 15:19.805
this can bias the data that we collect.

15:20.315 --> 15:23.645
Another common, solution

15:23.645 --> 15:26.565
that the enumerators used was emphasizing their political

15:26.565 --> 15:29.005
or ethnic identity to be able to kind

15:29.005 --> 15:31.125
of make the respondent comfortable.

15:31.505 --> 15:34.125
But what that can do is influence the respondent's answers,

15:34.555 --> 15:37.365
even if it does protect the enumerator themselves.

15:37.585 --> 15:40.605
And so in general, we show that greater exposure to violence

15:41.065 --> 15:43.765
or working in violence affected communities correlates

15:43.765 --> 15:44.965
with an increased likelihood

15:44.965 --> 15:47.005
of deviating from survey protocols

15:47.585 --> 15:50.525
and across a range of, of various variables,

15:50.525 --> 15:52.885
that we show in the paper in numerous face.

15:53.125 --> 15:55.525
Personal insecurity during data collection report,

15:55.525 --> 15:58.525
more challenges from local populations, express difficulties

15:58.555 --> 16:00.205
with some types of survey questions

16:00.545 --> 16:02.525
and deviate from the research protocol.

16:02.865 --> 16:04.845
Oh, I just wanna add one thing about implications,

16:04.845 --> 16:06.045
which I think is that sort of,

16:06.045 --> 16:07.925
and this is gonna sort of build on something Justine just

16:07.925 --> 16:10.245
said, which is I think one key finding for us

16:10.635 --> 16:13.325
that is takes a sort of step away from the enumerator is

16:13.325 --> 16:15.165
that it's often survey respondents

16:15.165 --> 16:16.365
who are posing the biggest hurdles

16:16.365 --> 16:18.205
and obstacles to survey enumerators.

16:18.505 --> 16:21.405
So as Jesse mentioned in open-end questions, they,

16:21.495 --> 16:24.085
about 50% of our enumerators said that, you know,

16:24.085 --> 16:26.245
mentioned some problems that they'd had with respondents

16:26.245 --> 16:28.005
and how hard it's to get, you know, respondents

16:28.005 --> 16:29.885
to complete interviews, to, to consent to interviews,

16:29.905 --> 16:31.885
to understand what they're there for, et cetera.

16:32.345 --> 16:33.565
And so, you know, as much

16:33.565 --> 16:35.485
as this paper is about enumerators,

16:35.545 --> 16:38.045
we think there's this sort of secondary implication about

16:38.255 --> 16:39.485
respondent hesitancy,

16:39.485 --> 16:40.565
which is something researchers

16:40.585 --> 16:41.925
should all be concerned about.

16:42.265 --> 16:43.965
So of course, some of this might be

16:43.965 --> 16:45.845
because of research fatigue.

16:45.905 --> 16:48.405
We know that in some communities, researchers, you know,

16:48.405 --> 16:50.245
there's certain work in like refugee camps that, you know,

16:50.365 --> 16:51.685
researchers are constantly running, you know,

16:51.825 --> 16:53.805
and not just researchers, but also like the un like

16:53.965 --> 16:55.085
everyone's running a million surveys

16:55.085 --> 16:56.565
and people just get tired of participating.

16:56.945 --> 16:59.085
That's one problem. There's also, of course, an issue

16:59.085 --> 17:01.965
of institutional trust that, you know, is, is, you know,

17:02.015 --> 17:03.925
often low in many of these settings,

17:04.225 --> 17:06.525
but we also think that there's a misunderstanding about the

17:06.725 --> 17:07.725
research process in general

17:07.835 --> 17:11.405
that I think says something about our failure as researchers

17:11.405 --> 17:14.445
to sort of translate why we're, you know, our results back

17:14.445 --> 17:16.405
to communities and to help them understand why there might

17:16.405 --> 17:18.325
be some value to what we're doing.

17:18.985 --> 17:21.605
Um, and so in this sense, we, I just wanna reiterate

17:21.605 --> 17:23.725
that I think that, you know, we think there's implications

17:23.725 --> 17:26.405
here for how we work with, you know, the people we hired

17:26.545 --> 17:28.485
to collect the data that we're interested in.

17:28.705 --> 17:30.965
But we also think that there's implications here for sort

17:30.965 --> 17:33.685
of, you know, why respondents don't really wanna partake in

17:33.805 --> 17:35.165
research that they don't see any benefit from,

17:35.165 --> 17:36.885
or they don't necessarily fully understand.

17:37.025 --> 17:40.165
And, and that that's also something that we, you know,

17:40.315 --> 17:42.525
hope people will sort of start taking seriously.

17:42.745 --> 17:44.005
But also think about sort of

17:44.105 --> 17:45.805
how respondents do understand

17:45.805 --> 17:47.005
the research that they're taking part in.

17:47.465 --> 17:49.885
One of the things we really wanted to do at this paper is

17:49.885 --> 17:53.725
to like, not just kind of detail all of the challenges

17:53.725 --> 17:54.805
that these enumerators face,

17:54.805 --> 17:56.205
but to actually offer solutions.

17:56.625 --> 17:58.965
Um, and so we have kind of a lengthy,

17:59.395 --> 18:01.845
implication section with a broad range of solutions.

18:02.225 --> 18:03.725
So first we urge researchers

18:03.725 --> 18:06.805
to continue efforts towards establishing disc disciplinary

18:06.935 --> 18:09.325
norms around research and insecure settings.

18:09.515 --> 18:10.685
This is already happening.

18:10.905 --> 18:14.325
Um, there's ad hoc committees on ethics across,

18:14.435 --> 18:17.405
political science, but we wanna keep pushing that

18:17.405 --> 18:20.845
and especially think thinking about our, enumerators.

18:21.685 --> 18:25.725
Secondly, we hope that our findings offer a call

18:25.785 --> 18:27.525
to alter our research designs

18:27.745 --> 18:29.605
to minimize risk to field staffs.

18:29.825 --> 18:31.445
And there's a lot of ways that we can do this.

18:31.545 --> 18:34.645
So, it can include being attentive to the timing

18:34.745 --> 18:35.965
and content of surveys.

18:36.075 --> 18:38.685
Enumerators said that it's kind of the worst timing

18:38.865 --> 18:40.885
to do a survey in a polarized

18:41.485 --> 18:43.285
insecure setting right before an election.

18:43.625 --> 18:46.405
And often in political science, we don't actually need

18:46.405 --> 18:47.645
to do it right before an election.

18:47.645 --> 18:49.165
Sometimes we're testing a mechanism.

18:49.705 --> 18:52.765
Um, we're just collecting data on political opinions outside

18:52.765 --> 18:54.325
of the electoral, setting.

18:54.665 --> 18:57.845
And so perhaps we can move our surveys up by a few months

18:58.265 --> 19:00.805
and reduce the risk that enumerators are seen

19:00.805 --> 19:01.925
as political actors.

19:02.865 --> 19:05.765
Um, we also encourage researchers

19:05.825 --> 19:08.325
to stay informed about enumerators working conditions.

19:08.585 --> 19:11.845
Um, as Martha mentioned, there is a distance often

19:11.895 --> 19:14.605
where we only interact with the survey firms,

19:14.665 --> 19:16.925
so we don't actually know how much the enumerators are being

19:16.925 --> 19:20.045
paid, whether they can get health insurance,

19:20.045 --> 19:22.285
whether they, are able to leave

19:22.385 --> 19:24.045
and not face any consequences.

19:24.505 --> 19:27.205
Um, and so understanding the working conditions,

19:27.425 --> 19:29.405
can help a alleviate some of these risks.

19:30.225 --> 19:33.365
Um, another thing we encourage is including enumerators in

19:33.365 --> 19:35.845
all aspects of the research design to make sure

19:35.845 --> 19:37.965
that we're asking culturally sensitive questions

19:37.965 --> 19:39.765
that are adapted to local realities.

19:40.105 --> 19:42.685
Um, so piloting the questions with the enumerators,

19:42.905 --> 19:45.245
asking them, you know, should I ask the question this way

19:45.265 --> 19:47.965
or that way, can help improve,

19:48.105 --> 19:50.285
not just their experience, but also the data quality.

19:50.345 --> 19:52.605
So we don't have enumerators changing the wording

19:52.605 --> 19:53.685
of questions on the fly.

19:53.875 --> 19:55.725
Instead everyone's asking the same question

19:55.725 --> 19:57.725
that's been adapted to the local context.

19:58.945 --> 20:02.885
Uh, one thought, that can improve, especially the fact

20:02.885 --> 20:03.885
that we, we see

20:03.885 --> 20:06.765
that enumerators felt particularly psychologically taxed

20:06.765 --> 20:09.685
by this research is considering psychosocial support

20:09.705 --> 20:12.445
for field staff, in country if possible.

20:13.065 --> 20:16.005
And then finally collecting data on enumerator experiences

20:16.005 --> 20:17.765
before and after the data collection.

20:18.145 --> 20:19.605
Um, we're the first to do this.

20:19.865 --> 20:22.005
Um, but there's ways that,

20:22.605 --> 20:24.605
researchers can improve if they collect data

20:24.625 --> 20:27.245
before, if they say, have you ever experienced violence?

20:27.305 --> 20:28.325
If the enumerators have,

20:28.325 --> 20:31.285
they can ask them more questions about how can we help you

20:31.345 --> 20:32.645
to avoid these contexts?

20:32.905 --> 20:35.645
Um, and then finally, after the research, we wanna make sure

20:35.765 --> 20:38.365
that, the enumerators are working in a safe environment.

20:39.025 --> 20:43.005
And so we hope that our paper contributes to,

20:43.035 --> 20:44.125
both our understanding

20:44.345 --> 20:46.965
and renders these enumerators experiences visible.

20:47.665 --> 20:51.125
Um, but that also we can improve both the way

20:51.125 --> 20:54.045
that data's collected and protect these enumerators

20:54.625 --> 20:58.165
and also, improve the data validity of our projects.

20:58.785 --> 21:00.565
You know, often as researchers, we spend a lot

21:00.565 --> 21:01.685
of time working on our surveys

21:01.685 --> 21:03.405
and especially if there's an experimental treatment

21:03.405 --> 21:05.205
of any kind, you know, really workshopping

21:05.385 --> 21:07.085
to make sure everything is, is tight and,

21:07.105 --> 21:09.125
and sort of doing what we hope it's doing.

21:09.665 --> 21:12.205
And so I think it can be hard if you're training enumerators

21:12.235 --> 21:13.965
that suddenly people are sort of saying, well this is,

21:13.965 --> 21:15.485
makes this, you know, to sort of be like, you know,

21:15.755 --> 21:17.645
it's last minute, you already have IRB approval, right?

21:17.645 --> 21:19.645
That this can pose challenges on our end.

21:19.645 --> 21:21.845
And I think sometimes it can lead to a reticence to sort of

21:22.455 --> 21:24.885
adapt things too much when we've spent, you know, months

21:24.885 --> 21:26.205
and months working on surveys.

21:26.505 --> 21:28.365
But on the other hand, I think, you know, if

21:28.365 --> 21:30.925
what we care about is capturing the reality,

21:30.925 --> 21:32.765
then I think we should be really open to these things.

21:32.905 --> 21:35.085
So, I mean, it's not a insecure context,

21:35.145 --> 21:37.085
but I was writing a survey in Senegal this past summer

21:37.185 --> 21:39.685
and the survey new had amazing suggestions for sort of,

21:39.685 --> 21:43.205
how do you know, come up with more, locally

21:44.485 --> 21:47.125
accurate sort of examples of practices

21:47.125 --> 21:48.125
that I was interested in asking

21:48.125 --> 21:49.685
with my co-authors asking questions about.

21:49.705 --> 21:51.125
And some of 'em said, you know, we know this happens

21:51.125 --> 21:52.285
elsewhere in Senegal,

21:52.285 --> 21:54.365
but in the area that we're working, here's a better idea.

21:54.785 --> 21:56.445
And, you know, that made the survey a lot better

21:56.465 --> 21:58.645
and it, I think it helps us get better data, right?

21:58.705 --> 22:01.285
And so I think it can, I,

22:01.445 --> 22:03.485
I understand why sometimes there's a bit of a hesitancy

22:03.825 --> 22:06.445
to sort of involve enumerators too much in the feedback,

22:06.445 --> 22:07.965
but I think we should also lean into the fact

22:07.965 --> 22:10.165
that these are experienced individuals who know the context,

22:10.545 --> 22:11.925
who, you know, I think are committed

22:11.925 --> 22:14.405
to having a good survey experience for everyone, including

22:15.085 --> 22:16.285
researchers getting the data that they want.

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