How has precarious employment been measured in the past?

In PEPiN NERD BLOG POST #1, we unpacked (or explained) our answer to the question “Why is PEPiN collecting data on precarious employment?” However, our answer probably left many readers asking, “Yes, but don’t we already know we have precarious employment in Niagara?” The answer to this new question is simple: current employment statistics at the provincial or Federal level do not measure precarious employment directly.

Instead, current employment statistics use proxies to measure precarious employment. What is a proxy? A proxy is a measure of one thing that is used to stand in for another related thing. One common example of a proxy measure is the use of years of education for the kinds of skills someone possesses. While we would assume that someone who completed high school, college or university is literate and numerate, we don’t actually know that for certain. We haven’t tested their literacy or numeracy skills, we just asked how many years of education they completed. While we take it to be reasonably likely that persons completing high school, college or university possess some literacy or numeracy skills, measures of years of education don’t actually measure numeracy or literacy skills.  

The same thing happens with precarious employment. We assume a connection between what is measured, and what was actually measured. However, with proxies, we don’t verify the connection. More common proxies for precarious employment include the unemployment rate, part-time work, service sector work, and single-parent households. Table 1 shows these.

While a simple solution to our problem would be to ask “Are you precariously employed?”, this wouldn’t actually be a very reliable measure, either. The term is not well-defined in the popular imagination. This is because precarious employment takes place in different ways and in different intensities. In turn, this means we need to measure each of the possible ways it could happen. Nerd Blog #3 will discuss how we measure employment precarity.

Why is PEPiN collecting data on precarious employment?

PEPiN stands for Poverty and Precarious Employment in Niagara. PEPiN is collecting data on precarious employment in Niagara because there are no reliable or valid measures of precarious employment in Niagara. In this blog post, I explain in plain English what this sentence means.

First, let’s define what we mean by precarious employment. As our telephone survey script reveals, precarious employment takes many forms:

Precarious employment means work that is some combination of part-time, without benefits, seasonal, variable income, on-call, on a limited-term contract or is performed by an owner-operated firm without employees. Thus, there are many kinds of precarious employment. This includes everything from farm workers to waitresses to substitute teachers to computer programmers.

In other words, not everyone in precarious employment is a high school student working at a low-wage fast-food restaurant. Increasingly, precarious employment is reported to be happening outside of the retail sector. Many people (especially those with a standard employment contract) might find this development surprising. Furthermore, not all forms of precarious employment are low-wage.

To help capture this spectrum, the PEPSO report measures precarious employment on a spectrum defined by ten (10) questions, none of which refer to amount of income. The more questions one answers affirmatively, the more precarious is one’s employment, regardless of industry or occupation (we will cover this in a later blog post, but if you are impatient, you can see them in Appendix B of The Precarity Penalty). Building on the shoulders of giants, we adopt this measure as well.

Second, let’s explain what reliable and valid actually mean. A reliable measurement is one that measures the thing being measured in a consistent way. If every reading of my bathroom scale swings wildly within 100 pounds of my weight, the scale does not produce a very reliable measure. If, on the other hand, the weight reported tends to vary little from reading to reading when I get off and then get back on it, then the measure is fairly reliable. A valid measurement is one that actually measures the thing it seeks to measure, and not something else. If my bathroom scale mysteriously measures how many minutes I slept the night before instead of my weight, this measurement is not valid. If however, it consistently measures only my weight, it is valid.

However, just because a measure is reliable doesn’t mean it is valid, and vice-versa. Let’s continue with the bathroom scale analogy. In the first example above, my unreliable bathroom scale does produce a valid measure. It measures my weight. However, it does not measure my weight in a consistent fashion. The first time I step on, I weigh 164 pounds. The next minute, I register 323 pounds. The third time in as many minutes, 100 pounds. In the second example, my bathroom scale produces a reliable measurement of how many minutes I slept the night before. It does this reliably every time I step on it. Unfortunately, my clock does that, too. As a bathroom scale, it is supposed to measure my weight. Not time sleeping. Thus, its measurement is not valid.

In both these examples, the bathroom scale is the ‘instrument.’ During PEPiN’s first stage of data collection (which began in mid-May) the telephone survey is the instrument. This survey consists of seven (7) sets of questions (we discuss these in a later post). The answer to each question becomes a measurement. These survey questions were modeled closely after another survey instrument designed by McMaster University’s Professor Wayne Lewchuk and his colleagues at PEPSO and the United Way of Toronto and York Region and used to collect data on precarious employment in the Greater Toronto Area and Hamilton. The findings from analyzing these data were published in PEPSO’s 2015 report called The Precarity Penalty.

Finally, let’s define ‘Niagara.’ Niagara refers to the twelve (12) municipalities in Niagara . If your browser runs Java, and you want to test your knowledge about Niagara’s basic geography, click here.

Some measures of Niagara’s economy only focus on the St. Catharines Niagara Census Metropolitan Area (CMA). This excludes two (2) of Niagara’s fastest growing regions, Grimsby and West Lincoln. By including all twelve (12) of Niagara’s municipal governments, and the Regional Municipality of Niagara, Niagara’s policy makers gain a more encompassing understanding of how precarious employment might or might not vary across our twelve municipalities.

In summary, we’ve explained why PEPiN is collecting data on precarious employment in Niagara. In the next blog post, we will also explain why anyone would want to do this.

BLOG #1 REFERENCES
Vosko, Leah (Ed.) (2006) Precarious Employment Understanding Labour Market Insecurity in Canada. Montreal : McGill-Queen’s University Press.

In 2016, the United Way Niagara Falls and Greater Fort Erie contacted Brock’s Social Justice Research Institute to see if any of its members would be interested in collaborating on a project to examine the type and extent of precarious employment in Niagara.

Precarious employment refers to employment that is not what is sometimes called the Standard Employment Contract. This refers to a permanent, full-time job that pays a living wage with benefits. Thus, precarious employment refers to work that is some combination of part-time, without benefits, seasonal, variable income, on-call, on a limited-term contract or performed by an owner-operated business without employees. In short, there are many kinds of precarious employment. This includes everything from farm workers to waitresses to substitute teachers to computer programmers. Furthermore, sometimes people take precarious employment when they would rather have a standard employment contract; sometimes they prefer precarious employment to a standard employment contract.

This study, (which is designed to be comparable with the results of a report published in 2015 on precarious employment in Hamilton and the Greater Toronto Area) will allow us to understand how widespread precarious employment is in Niagara, the various forms it takes and how this impacts those in precarious employment, and if it is different from precarious employment in Hamilton and Toronto. This information is useful to the United Way Niagara Falls and Greater Fort Erie because it helps with understanding the needs and experiences of Niagara’s residents.  However, this information should also be useful for local governments, non-profits, schools and employers as they develop their own labour market and social service policies. We might also use this information to write academic papers about precarious employment.

To collect the relevant data on workers’ experience with precarious employment, the lead researchers (Jeff Boggs and Jonah Butovsky) rely on two techniques: telephone surveys and interviews.

The first data collection technique is a telephone survey. Leger has been contracted to contact a random sample of Niagara telephone numbers and conduct the survey for the lead researchers. This survey is voluntary, and lasts about 20 minutes. Thus, only respondents who give consent to be surveyed are surveyed. Giving consent means that respondents are allowing the researchers to collect and analyze the data to better understand precarious employment in Niagara. We collect the data by asking questions about an individual’s paid work, unpaid work, housing, education, stress and health. These responses will be kept confidential, and in many cases will also be treated as anonymous. We maintain confidentiality by separating an individual’s phone number (and first name, if that is needed for a call-back to complete the survey) from their response before analyzing the data. Furthermore, because we are looking for trends in the responses, similar individual responses will be grouped together. Given we aim for 700 completed surveys, nobody will be able to identify any one person’s answers to the survey questions. While future researchers might also use the data, they would have no access to the names or phone numbers, rendering the identities of participants anonymous.  In instances where we think that other responses (i.e., answers to a specific question) would likely jeopardize a respondent’s anonymity, we would also suppress that particular response.

At the end of the telephone survey, respondents will be asked if they would like to participate in an interview one to three months later (conducted either in person or on the telephone, depending on scheduling and the respondent’s preference). This is the second data-collection technique. Consenting to a telephone interview allows respondents to go into more detail about their own precarious employment experience. All interviews will be conducted by a Brock research assistant. The interview will be recorded and transcribed. To keep the interview on track, the research assistant and researchers might design personalized questions based on the interviewees survey responses. These questions [i.e., what we call ‘probes’] will be designed to create a conversation about the interviewee’s precarious employment experience. This could last up to an hour, depending on the respondent’s interest. After being transcribed, the interviews will be analyzed for additional trends. In some cases, snippets from interviews will be used to illustrate particular trends or experiences in the final report and academic papers. While conversations about precarious employment may well be more personal than the survey, we insure all respondents’ confidentiality.

This entire research process is overseen and sanctioned by Brock University’s Research Ethics Board (REB). Our REB application file number is 16-236.  The REB application and monitoring process insures that we conduct ourselves ethically while conducting this research and handle the data accordingly. This includes protecting the data from data breaches by keeping copies of the data in a locked room on computers behind an Internet fire wall, as well as maintain respondent’s confidentiality.