The two research metrics, this one and Research revenue attracted from private sector sources<\/em>, have a different target settings process than other metrics. <\/p>\n\n\n\n The targets are simply a rolling average of the previous three years, minus the band of tolerance. <\/p>\n\n\n\n SMA3\u2019s Research funding & capacity: Federal Tri-Agency funding secured metric is a more sustainable target settings method for the zero-sum research revenue attracted from private sector sources metric measure because it is not structuring each university to consume the others portions as a mandate (though Tri-Agency funding itself remains competitive). SMA3 documents also provide the real dollar amounts separately from the historical data. Institutional research offices regularly provided this information publicly, including in reports to the Canadian Association of University Business Officers (CAUBO)<\/a>.<\/p>\n\n\n\n Only a few American PBF programs have a similar metric, for example, Tennessee has a research, service, and sponsored programs metric, which is defined as the \u201cexpenditures on activities for research, service, or instruction. Financial aid, capital funding, state appropriations, donations from foundations, and practice income are excluded from this outcome\u201d (Wilson et al., 2020, p. 9<\/a>). Tennessee\u2019s measure is more of a measure of nonteaching expenditure, not a measure of success in the institution\u2019s research mission.<\/p>\n\n\n\n The literature on PBF programs in America examines the general impact of declining funds and the distorting impact of PBF metrics on teaching-related areas such as admissions but does not identify any effects on research beyond general impacts on budgets and activity.<\/p>\n\n\n\n Europe has had different forms of performance-based research funding for some time, both for universities and for dedicated research institutions. The European Union\u2019s 2011 policy document, Supporting Growth and Jobs\u2014An agenda for the Modernisation of Europe\u2019s Higher Education Systems <\/em>(Directorate-General for Education and Culture, European Commission, 2011<\/a>), has encouraged \u201ca better identification of the real costs of higher education and research and the careful targeting of spending, including through funding mechanisms linked to performance which introduce an element of competition\u201d (p. 13). <\/p>\n\n\n\n EU member states have implemented different forms of PBF for research in parallel and directly as part of PSE funding. These research PBF programs, in particular, the United Kingdom\u2019s Research Excellence Framework have de-emphasized teaching and led to unintended negative consequences (Bishop, 2020<\/a>). <\/p>\n\n\n\n Performance metrics and targets that measure and reward paper publications or citations have in some cases reduced the impact of the associated papers. This practice also can incentivize so-called \u201csalami\u201d style research publication; that is, slicing up the results of research in an attempt to increase the publications yielded from the same research (Jonkers & Zacharewicz, 2016<\/a>).<\/p>\n\n\n\n By aggregating the Tri-Agency funding, there is less incentive for institutions to game the metric (research funding and capacity: Federal Tri-Agency funding secured) or alter institutional research strategies beyond factors that would otherwise be relevant to institutions with two notable exceptions: <\/p>\n\n\n\n The average weighting for this metric is 13% in the first year and 8% in the subsequent years. The most often used weighting is 10% in the first year and 5% in the subsequent years. Universit\u00e9 de Hearst does not participate in either research metric.<\/p>\n\n\n\n The total of all historical data adds up to 99.10% of all Tri-Agency funding allocated to Ontario in 2016\u201317, 98.94% in 2017\u201318, and 98.78% in 2019\u201320.<\/p>\n\n\n\n Presumably, the remainder for each year is awarded to other Ontario-based institutions such as colleges, hospitals, and private firms. <\/p>\n\n\n\n The allowable target for 2020\u201321 adds up to 95.43%. <\/p>\n\n\n\n The University of Toronto consistently represents over a third of Tri-Agency funding awarded in Ontario, reflecting the 16% that the University of Toronto is awarded nationally (University of Toronto & MCU, 2020, p. 16). This is an example of why an average-only target setting model is more appropriate to this metric, as the University of Toronto\u2019s or Queen\u2019s University\u2019s variances would set targets that would consume Algoma\u2019s share within two years.<\/p>\n\n\n\n Institutional narratives described the research activity at each institution, alignment to strategic plans, and institutional success in rankings in publications that ranged from Maclean\u2019s<\/em>, to The Times Higher Education<\/em>, to Research Infosource rankings, to Nobel prizes.<\/p>\n\n\n\n McMaster University, the University of Toronto, the University of Waterloo, and Western University all weighed this metric highly, with Western University weighting consistently at the maximum available. These institutions cited constancy as the primary reason for the weighting allocation. Carleton University weights all dynamic metrics at 11%. All other universities weighted the metric at the lowest possible weight, with Laurentian University providing insight into its weight that \u201cLaurentian has been able to attract Tri-Agency funding; however, we are concerned about the volatility of this metric given our connections to resource-based industries, including mining\u201d (MCU & Laurentian University, 2020, para. 97<\/a>).<\/p>\n\n\n\nAmerica PBF research metrics<\/h2>\n\n\n\n
European PBF research metrics<\/h2>\n\n\n\n
What does this mean for University research?<\/h2>\n\n\n\n
Implementations of the research funding & capacity: Federal tri-agency funding secured metric<\/h2>\n\n\n\n
![\"\"](\"https:\/\/mattclare.ca\/pse-policy\/wp-content\/uploads\/2021\/12\/research-funding-877x1024.png\")
<\/figure>\n\n\n\nTabular version of Tri-Council funding<\/h2>\n\n\n\n