An Investigation Into Repeat Requests for Charity: Evidence From the St Vincent de Paul Society Queensland,Australia

Abstract

In advanced industrialized economies, charitable organizations work alongside formal social services provided through welfare states to assist people living in poverty. The work of charities with socially and economically marginalized people, however, often takes place in the absence of robust evidence about what impact charity has on people’s lives. This study draws on a large administrative database to investigate what determines repeat requests for charity and how people may achieve dignity. Our findings show that frequent residential address changes seem to make people more reliant on charity, whereas the more time spent with people receiving charity significantly decreases repeat requests for charity. We propose that the provision of charity can be an opportunity to promote connectedness.

Keywords

charity evidence administrative data

Introduction

Throughout advanced industrialized economies, charitable organizations work alongside formal social services provided through welfare states to assist people living in poverty (Lynn, 2002; Smith & Lipsky, 1993). In this regard, Australia is no different (Mendes, 2009). The Australian government aims to fulfill its mandate to ensure basic rights and an acceptable standard of living, and a requirement to protect and support vulnerable people in society (Steering Committee for the Review of Government Service Provision [SCRGSP], 2017), in part, through the provision of approximately Aus$100 million each year to fund services through more than 400 service providers. Among other functions, this support is aimed to help people address their immediate needs in times of financial crisis through the provision of emergency relief (Department of Social Services, 2017). Charities in Australia perform a similarly diverse range of activities of which the provision of emergency relief is just one aspect (Cortis et al., 2016). However, little is known about how effective these efforts are.

Despite the complexities of responding to people in need and the partial role that charity can play in addressing poverty, it is critical to generate an evidence base about what impact charity has on people receiving it. Even in secular societies, governments fund what are often faith-based charities (Wuthnow, 2004). Despite the receipt of state funding, governments recognize the evidence about the effectiveness of charity is limited. Moreover, early findings produced using Australian Government data demonstrate that 17% of people are presenting to charitable organizations seeking emergency relief 5 or more times within a 6-month period. This finding has motivated policy makers to ask whether or not responses could be better directed at prevention (Department of Social Services, 2017).

The purpose of this study is to investigate repeat requests for charity, measured in terms of repeat requests for emergency relief specifically. Our analysis is driven by research with an Australian nonprofit charity. Australia’s nonprofit footprint comprises 57,000 organizations, employing 8% of the working population, countless volunteers, and contributes nearly Aus$60 billion to Australia’s GDP (Haski-Leventhal & Foot, 2016). The St Vincent de Paul Society (SVdP) is a lay Catholic Church (faith-based) organization, which has global reach, a history in Australia stretching back to 1854 (Camilleri & Winkworth, 2005), and is one of Australia’s major providers of charity. For SVdP (2017), Queensland emergency relief assistance accounts for a significant portion of their activities, which amount to operating expenses of Aus$8,122,238 in the financial year ended June 30, 2017. To provide emergency relief support, the SVdP, Queensland, does receive some government funding, except for conferences in and around the State’s capital city, Brisbane, which rely on the generosity of donors and proceeds from SVdP’s retail “op shops.” SVdP, Queensland, is represented by 202 conferences, or organized groups of volunteers, based around local parishes and churches, where they provide their charitable assistance. These conferences, and their constituent volunteers, mobilize by responding to requests for emergency relief recorded in an administrative database by call-center workers and volunteers. Following the provision of assistance, volunteers record their actions in the administrative database. As explained below, the conference-level data—recording requests for, and responses to, emergency relief—drive the analysis in this article.

This study aims to contribute evidence of the impacts of charity. We focus on understanding what drives and reduces repeat requests for charity, based on the assumption that repeat requests represent a continued need, material, or otherwise (e.g., a need for social interaction), and conversely no further request indicates a successful intervention. Thus, we first ask, what determines repeat requests for charity? Second, does the time a volunteer spends providing charity with the people receiving help have an impact on repeat requests for charity?

Charity and Recipients

In advanced industrialized economies, we have a well-developed body of evidence about charitable organizations, including the motivations of people giving charity (Fong, 2007), strategies to gain funding (Das, Kerkhof, & Kuiper, 2008), and how public policy influences and indeed supports charitable social service provision (Brooks, 2004). In countries with advanced welfare states, however, we have surprisingly little evidence whether, and if so how, charity benefits people living in poverty (Mohan & Breeze, 2016). Staff in charitable organizations see measuring outcomes a necessity for their funders, not for the people accessing and ideally benefiting from charitable services (Benjamin, 2012). Indeed, reporting charity’s outcomes is often motivated by legitimizing the organization rather than promoting the interests of people receiving charity (Hyndman & McConville, 2016).

Driven by the effective altruism movement, Peter Singer (2016) has drawn attention to relatively recent Metacharity initiatives that seek to measure and report the effectiveness and costs of charities, predominantly operating in developing nations (see also Hyndman & McConville, 2016). Metacharities seek to influence where donors give by analyzing and reporting how much it costs charities to save a human life, for example, through the provision of malaria nets. Focusing on Australia, a rich country with a developed welfare state by international standards, our research aims to inform the emerging drive to have an evidence base about what charities achieve.

Furthermore, our research seeks to identify an alternative way forward for independent researchers to assess the impact of charity. It represents a genuine opportunity to address the criticisms of scholars, activists, and aid providers leveled at the effective altruism movement’s predilection for randomized controlled trials (Cochrane & Thornton, 2016; Gabriel, 2017). To address these gaps in the literature, and our specific research questions, we utilized the administrative data obtained by SVdP.

Research Methodology

Data

The SVdP Queensland administrative database Support OnLine (SOL) contains information collected about interactions and assistance provided by the SVdP. October 2, 2006, was the inception of the database. This study uses data from the inception of the database to the November 30, 2016 (the most recent data available). The variables used throughout this study are extracted from this database at the conference level. At the time of writing, 202 conferences were active, organized within regional councils, diocesan central councils, and the State council. In all, a balanced panel of 79 conferences for the years 2009 to 2016 is used for the regression analysis.

Key variables

Requests are generally received initially through the Helpline and are typically made for food, finance, furniture, and/or clothing. Each of these requests may be attributable to one or more individuals, for example, an individual, a couple, or a family. Conference members respond to these requests. In some cases, this can involve many visits to those in need to provide assistance (e.g., food, food vouchers, clothing, a small loan for a refrigerator, or the payment of unexpected expense such a medical bills). A number of other services and programs are also offered by the SVdP and individuals may be referred to these where appropriate or other external government or community organizations. The dependent variable of interest is the mean number of requests per person for a conference for a year.

The mean number of requests per person has remained steady over time. Figure 1 shows the patterns of requests. In 2016, on average, 2.54 mean requests per person, and in a more extreme case, 76 requests per person (Figure 2).

Figure 1.

Total requests in total and by type of request throughout Queensland, Australia (2006-2016).

Figure 2.

Aggregate requests where an individual returned for assistance within the following 12 months, 2, 3, or 5 years, throughout Queensland, Australia (2006-2016).

Moreover, the number of requests exhibits both temporal and spatial variation. Figure 3 provides a straightforward illustration of the spatial heterogeneity in total requests at the postcode level for 2016 throughout Queensland, Australia. The inset map of the Greater Brisbane Metropolitan area illustrates that the level of request are highest among postcodes in the State’s capital city (M = 2,346 requests) compared with the rest of the State (1,578 requests).

Figure 3.

Postcode-level requests throughout Queensland, Australia (2006-2016).

Several explanatory variables, drawn from the available data, were reasoned to be related to the mean number of requests per person for a conference for a year. These were sorted into four key groups: conference expenditure, accommodation, visits, and local area measures. Conference expenditure includes the dollar amount for different type of expenditures including furniture, Christmas hamper, bread run, cash, food conference (food bought by the conference), food other (donated food), other conference expenditure, vouchers, clothing, and household items. Accommodation includes the mean number of different addresses per person at the conference level and the visits are characterized by the length of visits. Local area measures include population density, the unemployment rate of the local area, and the spatial lag of the mean requests per person. Descriptive statistics for these variables are listed in Table 1. The supplementary information provides further details.

Table 1.

Descriptive Statistics of the 79 Conferences Using Pooled Data Across 8 Years From 2009 to 2016.

Variable name	Definition	Observations	M	SD	Minimum	Maximum
Dependent variables
Mean requests per person	Mean requests per person by conference and year	632	12.01	6.75	4.43	62.61
Conference expenditure
Furniture (‘0000 [Aus$])	Total furniture expenditure (‘0000 [Aus$]) by conference by year	632	2.53	4.46	0	25.92
Christmas hamper (‘0000 [Aus$])	Total Christmas hamper expenditure (‘0000 [Aus$]) by conference by year	632	1.52	4.40	0	42.24
Bread run (‘0000 [Aus$])	Total bread run expenditure (‘0000 [Aus$]) by conference by year	632	0.51	2.14	0	23.23
Cash (‘0000 [Aus$])	Total cash expenditure (‘0000 [Aus$]) by conference by year	632	0.37	1.14	0	9.17
Food conference (‘0000 [Aus$])	Total food conference expenditure (‘0000 [Aus$]). This is food bought by the conference by conference by year	632	3.45	8.52	0	57.79
Food other (‘0000 [Aus$])	Total food other expenditure (‘0000 [Aus$]). This is donated food by conference by year	632	0.94	2.39	0	18.93
Other conference expenditures (‘0000 [Aus$])	Total other conference expenditure (‘0000 [Aus$]) by conference by year	632	0.71	1.78	0	12.47
Vouchers (‘0000 [Aus$])	Total vouchers expenditure (‘0000 [Aus$]). This includes, for example, food vouchers, phone vouchers, and other vouchers (almost 90% of these vouchers are for food) by conference by year	632	10.31	12.47	0	70.83
Clothing (Aus$)	Total clothing expenditure (Aus$) by conference by year	632	3,469.09	6,325.72	0	45,316.36
Household (Aus$)	Total household expenditure (Aus$) by conference by year	632	1,504.89	3,202.50	0	20,239.95
Accommodation
Different addresses	Mean total number of different addresses of individuals by conference and year	632	2.36	1.08	1	13.23
Visits
Hours per visit	Mean number of hours per visit by conference and year	632	0.30	0.16	0.09	1.16
Local area measures
Population density (persons/ha)^a	Number of persons per hectare in SA2 of the conference by conference and year	632	15.42	12.27	0.01	65.35
Unemployment rate (%)^a	Unemployment rate of the SA2 of the conference by conference and year	632	6.82	3.46	1.30	23.60

Note. This source provides resident population estimates for the years between 2001 and 2015 at the SA2 level from 2001 to 2015. At the time of writing, the population figures for 2016 at the SA2 level were available and have been obtained from linearly extrapolation resident population estimates for the years 2001 to 2015. Note also that the small area estimates of the unemployment rate at the SA2 level are obtained from the years ending September 2012 to September 2016. Using census data from time series profiles from the ABS at the SA2 level, the years between the 2006 and 2011 Census were linearly interpolated (Department of Education, 2015). SA2 = Statistical Local Area 2; ABS = Australian Bureau of Statistics.

Note that the underlying data for the population density (persons/ha) measure are prepared by the ABS.

Analytic Strategy

This study employs a Poisson quasi-maximum likelihood estimator (QMLE) with continuous endogenous covariates estimated using the control-function estimator. This method takes account of the nonnormal distribution of the dependent variable and potential confounding influences, which mitigates the risk that the estimates are biased and inconsistent. The Poisson model is implemented using the Stata command ivpoisson in Stata/MP 14.2 (Wooldridge, 2009).

Identification

There are many potential sources of endogeneity, which threaten to confound the identification of causal impacts of the assistance provided by the SVdP on the degree of use of services. The potential for some unobserved factor (e.g., an individual’s interaction with complementary or substitute local community services) to lie beneath apparent associations is serious and could lead to incorrect inferences. This risk is mitigated by the adjustment of standard errors for clustering at the conference level, the inclusion of a spatial lag to account for the unobservable locational influences, the adjustment for population density, and the unemployment rate in the local area.

Simultaneity bias represents an issue by construction for spatial lags. This is because one conference may be influenced by and may influence a neighboring conference. The spatial lag is included in the model to abstract from potentially confounding omitted spatial variables. In addition, many of the independent variables are characteristics of the requests, which feature in the dependent variable. This represents another instance of simultaneity. This simultaneity demands a cautious interpretation of the independent variables, in terms of what activities promote and detract from mean requests for assistance per person at the conference level.

To address this issue of simultaneity as it relates to the hours per visit variable, an instrumental variable approach is taken to the analysis. Specifically, the variable hours per visit is instrumented using the first- and second-order temporal lags of the variable. The diagnostic test statistics are reported in the supplementary information. Importantly, the instrumental variables pass the required tests. There is no evidence to indicate that the instruments are themselves endogenous or that they are weakly identified. Beyond these diagnostic tests, which lend confidence to the instrumental variables, for the hours per visit variable, the temporal ordering of events severs the simultaneity that would otherwise plague the results as the present cannot predict the past.¹

Results

Descriptive Statistics

Table 1 provides precise definitions of the variables and their relevant descriptive statistics for the balanced data set of 79 conferences from the years 2009 to 2016.

On average, there are 12 mean requests per person by conference. The largest expenses for the conferences can be found for food with an average expenditure of Aus$34,500 per conference per year, and for furniture with an average expenditure of Aus$25,300 per conference per year. In regard to the accommodation, the mean total number of different addresses per person per conference lies at 2.36. The average time a volunteer spends with the person seeking help is 0.30 hr or 20 min.

Poisson Model

The main regression results, which address the research question, are reported in Table 2. The results are reported as incident rate ratios (IRRs) throughout. The interpretation of the IRR can be explained through the use of an example: A one-unit increase in food expenditure, which equates to Aus$10,000, is associated with 1% lower mean requests per person averaged at the conference level. In contrast, a one-unit increase in clothing expenditure corresponds on average to a marginally higher number of mean requests per person at the conference level. Our study has two headline findings. First, each increase in the number of different addresses an individual reports, averaged at the conference level, is associated with a 26% increase of requests per person, as averaged at the conference level. Second, the results point to a potential mechanism through which repeat requests for charity are mitigated. Specifically, the results demonstrate that, if the time volunteers spend providing assistance increases by 1 hr, on average, at the conference level, requests per person averaged at the conference level decreases by 25%. This is a substantial change.

Table 2.

IV Poisson Model Results.

	Mean requests per person
	IRR	95% CI	SE	p value	VIF
Conference expenditure
Furniture (‘0000 [Aus$])	0.99	[0.98, 1.00]	0.01	.07	5.42
Christmas hamper (‘0000 [Aus$])	1.00	[0.99, 1.01]	0.00	.83	2.35
Bread run (‘0000 [Aus$])	0.98	[0.96, 1.01]	0.01	.13	2.41
Cash (‘0000 [Aus$])	0.99	[0.97, 1.02]	0.01	.64	1.22
Food conference (‘0000 [Aus$])	0.99	[0.99, 1.00]	0.00	.00	2.49
Food other (‘0000 [Aus$])	1.03	[1.00, 1.07]	0.02	.06	4.32
Other conference expenditures (‘0000 [Aus$])	1.00	[0.97, 1.03]	0.01	.99	2.78
Vouchers (‘0000 [Aus$])	1.00	[1.00, 1.01]	0.00	.63	3.33
Clothing (Aus$)	1.00	[1.00, 1.00]	0.00	.03	5.32
Household (Aus$)	1.00	[1.00, 1.00]	0.00	.10	2.38
Accommodation
Different addresses	1.26	[1.20, 1.32]	0.03	.00	5.42
Visits
Hours per visit	0.75	[0.57, 0.99]	0.11	.04	4.24
Local area measures
Population density (persons/ha)	1.01	[1.00, 1.01]	0.00	.00	3.20
Unemployment rate (%)	0.99	[0.98, 1.01]	0.01	.48	5.13
Spatial lag
Spatially weighted lag mean requests per person	1.00	[1.00, 1.00]	0.00	.86	2.84
Year fixed effects
_2010	0.99	[0.96, 1.02]	0.01	.65
_2011	0.97	[0.88, 1.06]	0.04	.45
_2012	0.97	[0.89, 1.06]	0.04	.47
_2013	0.97	[0.87, 1.07]	0.05	.49
_2014	0.93	[0.83, 1.03]	0.05	.17
_2015	0.95	[0.85, 1.05]	0.05	.32
_2016	0.95	[0.85, 1.05]	0.05	.29

Note. Exponentiated coefficients (incident rate ratios [IRRs]); Standard errors adjusted for clustering of observations within conferences; 95% CIs in parentheses; Diagnostic test statistics are reported for the instrumental variables using a natural log-transformed dependent variable and are reported in the supplementary information. A sensitivity analysis was performed to explore whether the regression results may be sensitive to the inclusion of any one observation and found the variable to be consistently significant, not showing particular sensitivity to any one observation. This lends confidence to the estimates reported in Table 2. IV = independent variable; CI = confidence interval; VIF = variance inflation factor.

Boldfaced values are statistically significant at the 5% level.

Discussion and Conclusions

We have sought to contribute much-needed evidence on the impacts of charity (Department of Social Services, 2017), in particular, emergency relief. In doing so, we advance an outcomes orientation (rather than an unhelpful preoccupation with cost-ratios; Mitchell, 2014) and, at least in part, share the desire of Australian Charities and Not-for-profits Commission (ACNC; Karp, 2018) to prosecute the creation of knowledge and understanding on the effectiveness charity.

Our findings about housing instability as the most significant driver for people making repeat requests for charity are supported by the existing literature and underlie how housing insecurity and poverty interact and manifest in the need for charity. We showed that if the average total number of addresses per individual averaged at the conference level increases by one, we observe a corresponding 26% higher level of mean requests per person. People on welfare rely on food, clothing, furniture, and money from charities because State benefit payments amount to living below the poverty line. Similarly, there is increasing evidence of a working poor, the “precariat,” as Guy Standing (2011) has dubbed this emerging class. Thus, people in poverty often rely on volunteers and charities to subsidize day-to-day life (Engels, Nissim, & Landvogt, 2012).

The costs of housing are a major driver of poverty in Australia. Housing is the highest fixed expenditure for low-income households; of the 2.99 million Australians living below the poverty line, or 13% of the population, 42% resided in expensive yet insecure private rental housing (Australian Council of Social Services, 2016). Saunders (2017) demonstrates how, for a large section of the Australian population, high housing costs are the “difference between just getting by and being driven below the poverty line” (p. 753). Indeed, it is the increase in housing costs post 2007-2008 that has benefited some home owners, on one hand, and increased both poverty and inequality for many outside of home ownership, on the other hand (Saunders, 2017). In addition to unaffordable rents driving poverty, the experience of housing insecurity that pervades the lives of low-income private renters perpetuates poverty by subverting people’s capacity to benefit from resources and mainstream institutions that those of us securely housed take for granted (Desmond, 2016). Unaffordable and insecure housing thus pushes people into crises that manifest in repeat requests to charities for emergency relief.

The data derived from an analysis of interactions between people giving and receiving charity tell us more, however, than what we already knew about the nexus of poverty and housing insecurity driving the need for material aid from charities. Most significantly, we have shown that the time a volunteer spends providing charity is associated with an individual making a repeat request for charity. Although time has been investigated as a variable in previous charitable or nonprofit contexts (Mason, 2013), for example, the willingness to give time (van Ingen & Dekker, 2011) or why it is given (Gee, 2011), our significant finding, based on analysis of 440,290 incidences of the provision of charity, illustrates the impact of time provided by volunteers. As the time volunteers spent with people increases on average by 1 hr, at the conference level, this would correspond to a 25% reduction in the mean number of repeat requests per person averaged at the conference level, a finding which is statistically significant at the 5% level. This remarkable evidence, to our knowledge the first of its kind, suggests that the time spent by volunteers with people in need is fundamentally helpful at reducing further requests for charity. This raises two critical questions: One which we cannot answer, but the other which we can to some extent, by making some theoretical inferences.

The first question is, what has happened in the lives of recipients who do not make repeat requests? The abductive temptation is to say the provision of charity assisted in addressing in some ways the problems that underpin people’s request for charity from volunteers. But actually, from our data, we can make no such claim. We do not have data to demonstrate why people did not make repeat requests; our data cannot say what occurred in their lives after receiving charity. The researchers are now seeking to address this gap by linking the recipient’s data with national and state government administrative repositories so we can ascertain whether people’s income, housing, and other life circumstances changed. The empirical limitations in our knowledge notwithstanding, we are cautiously optimistic that not requesting further assistance is an indicator of some positive outcome. The evidence about housing insecurity and repeat requests does in fact suggest that repeat requests are a product of entrenched poverty (Engels et al., 2012), and thus not requesting again may indicate improvement, even if temporary.

The second question our analysis raises is, what is it about the duration of time spent by volunteers that explains people not making repeat requests? Why does the more time volunteers spend with individuals receiving charity reduce the likelihood for further charity requests? In the same way that we cannot explain what happened to people after receiving charity without linked administrative data, we cannot conclusively know what it is about the duration of time between the provider and receiver of charity that makes a difference because we do not have qualitative data about the exchange.

The interdisciplinary literature about loneliness and connectedness offers some provisional explanation. The evidence has long shown that social connections and a feeling of connectedness promote myriad positive health and well-being outcomes (Ambrey, Ulichny, & Fleming, 2017; Jetten, Haslam, & Haslam, 2012; Townsend & McWhirter, 2005). Although there is debate and competing evidence about how social relationships promote positive effects and what populations they do and do not work for, even brief social connections—when they are characterized by functional support—enhance well-being and people’s capacity to cope (Kawachi & Berkman, 2001). The time spent by volunteers may be experienced as a positive form of connection. In addition to the broad sociological and psychological literature, support for the theory that the time spent by volunteers promotes positive outcomes by fostering connectedness can be found in the social work and helping professions literature. People accessing charity want “individualised and personal” responses from charitable providers (Frederick & Goddard, 2008). Individual and personalized responses require time.

Eileen Munro’s (2011) review of the English Child Protection System demonstrates that social work is effective when service providers have the time and opportunity to build human relationships with the people they provide services to. Scholars in the field note that high standard social work practice is enabled when practitioners have sufficient time to work with families (Forrester et al., 2013). Murphy and colleagues provide a detailed theoretical account of what does and does not constitute evidenced relationship-based social work practice (Murphy, Duggan, & Joseph, 2013). They show that service providers use relationship-based practice for instrumental reasons to gain knowledge about the service user or relationship-based practice where the relationship is an end in itself. The former relationship-based practice serves the interests of the service provider, for example, by ascertaining information, whereas the latter is nondirective premised on the people as autonomously driving the direction and purpose of the exchange (Murphy et al., 2013).

Charitable support provided by volunteers to those experiencing disadvantage is nondirective and differs from the provision of formal social services that minimize the significance of relationships and instead focus on managing risks and management-directed outputs (Frederick & Goddard, 2008). The time spent with charity recipients may be determined by many contextual factors: the volunteer’s motivation, disposition or available time, the perceived “deservedness” or “likeability of the recipient,” or even the difficulty of assessing the nature of emergency relief to be provided; for example, clients with mental health, behavioral, or substance abuse issues may present as challenging. These challenges may result in longer or shorter visits. We do not know about the motivations and actions of the thousands of volunteers; in 2015-2016 alone, there were 6,761 registered volunteers with the organization. We do, however, know what formal theological doctrines underpin the SVdP. The Catholic Church quotes St Vincent de Paul as saying,

It is one thing to give charity. It is another thing entirely to give the sense of humanity and dignity and personhood. If the person you care for, leaves your care feeling more of a person than before you came along, you have succeeded. Only then. (cited in Cathedral Connections, 2015)

The approach of volunteers may bridge the Catholic doctrine of charity with the professional social work theory of unconditional positive regard. The nondirective approach of charitable provision where opportunities for relationships can be developed, although limited in myriad ways to address structural poverty, may help us understand why the longer the volunteers spend with people, the less likely the recipients are to make repeat requests. The time that volunteers spend and the relationships-based practice are not principally to serve another purpose, such as assessment on behalf of the state. The time spent by volunteers delivering charity is nondirective and can be considered person-centered, an end in itself (Murphy et al., 2013). Robert Wuthnow’s (2004) comprehensive analysis of faith-based charities and social services in the United States challenges some of the assumptions that faith-based organizations are more effective than secular providers. He does conclude, however, that faith-based charities and social services probably do achieve better outcomes for marginalized individuals when they deliver small congregation styled services where positive relationships can be developed. Following Wuthnow, our research adds to the literature on the impacts that volunteering has on volunteers (McBride, Lough, & Sherraden, 2012), and develops evidence about how volunteers in charities—through relationships developed through spending time with people—contributes to positive outcomes for recipients.

In this sense, the material relief that volunteers provide to the people in poverty and the time they spend with them, serves two purposes. On one hand, it acts as a temporary relief to the structural drivers of their poverty, and in this sense the food, clothing, blankets, and so on act as a proxy for the real underlying cause of their disadvantage. On the other hand, and in a more positive sense, the material provisions act as a tangible artifact that initiates the development of a relationship.

As signaled, our study has some constraints. Primary among these is that we have used data from a single charitable organization. Unique as this may be, the limitations imposed for the preservation of anonymity by our funders did not enable an individual-level analysis. Moreover, we have a current inability to link cases to other databases that would furnish a fuller picture of the life journeys and experiences of our sample, as illuminated by their interactions with other arms of the welfare state and/or nonprofits. Key to this data linkage would be opportunities to determine whether recipients of emergency relief from one charity also seek (or avoid) support from other nonprofits or providers of welfare. This study creates a rich starting point for future research that can navigate these opportunities.

Confidence in our headline finding, that time spent by volunteers with those seeking emergency relief reduces the likelihood of repeat requests, is borne out from the sheer volume of data and rigor of our methods. Yet, it in itself does not explain precisely what occurs in the passage of time spent, or indeed the motivations of those requesting assistance, for example, primarily companionship. We have looked to theoretical explanations for this finding but we can claim these to be empirically based in our data. This again presents future opportunities for qualitative or ethnographic research to investigate what it is in the passage of time that makes a difference. This study provides a foundation to explore new frontiers in the “good works” of charitable, nonprofit organizations as they impact the most vulnerable in society.

Supplemental Material

Supplementary_information_Ambrey_et_al – Supplemental material for An Investigation Into Repeat Requests for Charity: Evidence From the St Vincent de Paul Society Queensland, Australia

Supplemental material, Supplementary_information_Ambrey_et_al for An Investigation Into Repeat Requests for Charity: Evidence From the St Vincent de Paul Society Queensland, Australia by Christopher L. Ambrey, Cameron Parsell, Melanie Spallek and Richard N. S. Robinson in Nonprofit and Voluntary Sector Quarterly

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research was conducted with a grant from The St Vincent de Paul Society, Queensland.

Notes

ORCID iD

Cameron Parsell

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Christopher L. Ambrey’s research has had a long-standing focus on the well-being of vulnerable and disadvantaged groups using statistical and micro-econometric techniques.

Cameron Parsell is a social worker and sociologist by training and his expertise is homelessness and social service provision.

Melanie Spallek’s research focuses on social statistics, administrative and survey data, and domestic violence.

Richard N. S. Robinson’s research expertise includes hospitality and innovative employment strategies for disadvantaged young people.

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