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The Power of Numbers - Part 2 Ernie S. Boyko Director Library and Information Centre April 23, 2004 Presented to the: Data Liberation Initiative Atlantic Training Workshop
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Or The Power (and the Politics) of Numbers Ernie S. Boyko Director Library and Information Centre April 23, 2004 Presented to the: Data Liberation Initiative Atlantic Training Workshop
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Outline Power of numbers The theory The practice Some realities And a few things your mother never told you
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Statistics Canada (Not the only source of data but…) Central Agency to serve all levels of government and public in general Its job is to help Canadians better understand their country Population Resources Economy Society Culture
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Statistics Canada (cont’d) 360 statistical programs 1000+ products per year $533 million – authorized expenditure $110 million – voted netted expenditure $423 million - net
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92% of entire budget is allocated to statistical programs dictated by statutes, regulatory instruments and contractual obligations Statistics Canada (cont’d)
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Refer to ‘Statistics Canada’s Quality Assurance Framework Catalogue number 12-586-XIE (free) We will take a quick look at the stakeholder/client feedback process later But first, a few schematics How Does STC Manage the Statistical Process?
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THE big reason for data and statistics How do we get from information about Canada to decision making? Let’s look at how we get from data to decision making Let’s talk about Decision making
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Decision Making Data System Information System Inquiry System Information for Decision Makers Interpretation and Analysis Theoretical Concepts Reality Data Output Specification and Testing of Analytical Framework Measurement Operationalization Concepts
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Public versus private? The political process? Who are the Decision Makers?
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Representative Government Norman Ward(1) has said that perhaps the best definition of Canadian representative democracy comes from John Stuart Mill, for whom representative democracy meant: “…that the whole people, or some numerous portion of them, exercise through deputies periodically elected by themselves the ultimate controlling power, which, in every constitution, must reside somewhere.”( 2) 1 Norman Ward, The Canadian House of Commons: Representation, University of Toronto Press, Toronto, 1950, p. 4. 2 John Stuart Mill, Considerations on Representative Government, first published 1861, new edition, R.B. McCallum, ed., Basil Blackwell, Oxford, 1946.
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Three Case Studies How STC makes program decisions How DLI was established Farm Net Income concepts Decision making
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National Statistics Council 15 Professional advisory committees Bilateral arrangements with key Fed depts Chief Statistician working with DMs Fed-Prov Council Special liaison in areas of prov jurisdictions Business associations and labour unions STC Program Decisions
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International Organizations Feed back from Advisory Services/users Bilateral/multilateral discussions about cost-recovery projects (remember the $110m?!) Biennial/quadrennial program reviews Annual planning process STC Program Decisions Cont’d
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DLI Orientation, Queen’s University April, 2004 Data Liberation in 2004: How Did We Get Here? Ernie Boyko, Statistics Canada Wendy Watkins, Carleton University Ernie Boyko Wendy Watkins
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DLI Orientation, Queen’s University April, 2004 Background: The Environment of the 1980's uGrowing expenditure deficits uStatistics Canada undergoing managerial transitions uPaper publications uTechnology: mainframes, minis, tapes, datapac uCANSIM and flat ASCII files on tape uPublic Use Microdata Files
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DLI Orientation, Queen’s University April, 2004 1984!!! Brave New World uNew government in September 1984 uMajor program review uBudget and program cuts u1986 Census cut uCensus users informed uReinstatement of Census in return for $100M
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DLI Orientation, Queen’s University April, 2004 Birth of CAPDU (Canadian Association of Public Data Users) u $tatistics Canada data out of reach u CAPDU born in Washington, 1988 u Began as lobby group, but … v no lobbying experience v only 8 members u Required another approach
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DLI Orientation, Queen’s University April, 2004 Fall Out From Expensive Data u One-sided research v well-funded think tanks could afford data v alternative views not heard u Data use dropped v graduate students most affected u Grant money spent on data, not research u US data used in place of Canadian
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DLI Orientation, Queen’s University April, 2004 Data Liberation: Making it Fly u Working group led by SSFC v members from: research community Statistics Canada CAPDU research libraries Depository Services Programme
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DLI Orientation, Queen’s University April, 2004 Data Liberation: Making it Fly u Activities: v lobbying politicians v presentations to the bureaucracy v co-option of Treasury Board u After two years, a pilot project see http://www.ssc.uwo.ca/assoc/capdu/dli- training/2004_ontario.html
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Case Study # 3 Net Farm Income Cash Receipts Income-in-kind Supplementary payments Realized gross income (1 + 2+ 3) Operating and depreciation charges Realized net income (4 – 5) Value of inventory changes Total gross income ( 4 + 7) Total net income (8 – 5)
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19761981 1Cash receipts104,869189,247 2Income-in-kind8,4253,485 3Supplementary payments-- 4Realized gross income (1 + 2 + 3)113,294192,732 5Operating and depreciation charges69,968129,566 6Realized net income (4 – 5)43,32663,166 7Value of inventory changes16,97328,915 8Total gross income (4 + 7)130,267221,647 9Total net income (8 – 5)60,29992,081 Farm Net Income Farm Net Income ($ ‘000) PEI Source: Statistics Canada, Farm Net Income, 21-202, 1976, 1984
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Income in kind ($ ‘000) PEI 2 Income-in-kind 19761981 Dairy products342460 Poultry and eggs9575 Meat4141,246 Fruits and vegetables (2)846 Honey and maple products1116 Forest products716842 Wool0- House rent ***6,001n/a Total8,4253,485 Source: Statistics Canada, Farm Net Income, 21-202, 1976, 1984
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***Income-in-kind This item consists of the value of consumption of home grown products… The imputed house rent values that used to be included in income-in-kind are no longer included in the farm accounts. What happened to house rent? Who decided? ****
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Income in kind ($ ‘000) PEI 2 Income-in-kind 19761981 Dairy products342460 Poultry and eggs9575 Meat4141,246 Fruits and vegetables (2)846 Honey and maple products1116 Forest products716842 Wool0- House rent ***6,001n/a Total8,4253,485 Source: Statistics Canada, Farm Net Income, 21-202, 1976, 1984
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Data ARE used for decision making but there are a lot of other factors involved Decisions can be made at many different levels It is often harder to get permission than it is to get forgiveness Conclusions?
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