How does your electorate rate on franking credits, grants, charity health or political donations?
Know Your Place With Ausgovinfo:local |
AusGovInfo 14th Aug 2020 |
To find your local electorates in each page triggered by the buttons in the menu above, click on the black 'Locate' button and give the browser a moment to reload.
Alternatively, if you want all the data from all the projects in a single page, click an electorate from the drop down list. This shows grants, donations, franking credits, charity financials and interests all in the same page.
If you click through to the charities, grants or political donations project you will see that all these projects have been radically revammped to improve usability.
Franking credits calculated on the fly combining the Dividends Franking Credit (Individuals and Share Franking Credit (Partnerships) based on 2017-18 ATO data Table 6A. Other fields also provided by postcode from the same table.
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MP | Electorate | Party | Individuals | Partnerships | Total | |
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1 | ![]() | WENTWORTH | LIBS | 433.78 | 317.53 | 751.31 |
2 | ![]() | HIGGINS | LIBS | 330.15 | 326.50 | 656.65 |
3 | ![]() | CURTIN | LIBS | 234.23 | 375.46 | 609.69 |
4 | ![]() | GOLDSTEIN | LIBS | 212.65 | 183.63 | 396.27 |
5 | ![]() | WARRINGAH | IND | 225.75 | 150.09 | 375.84 |
6 | ![]() | NORTH SYDNEY | LIBS | 240.28 | 114.20 | 354.48 |
7 | ![]() | MACKELLAR | LIBS | 228.85 | 112.03 | 340.88 |
8 | ![]() | BRADFIELD | LIBS | 230.19 | 102.83 | 333.02 |
9 | ![]() | SYDNEY | ALP | 181.36 | 87.82 | 269.19 |
10 | ![]() | ADELAIDE | ALP | 145.72 | 114.82 | 260.54 |
11 | ![]() | RYAN | LNP | 127.74 | 112.12 | 239.87 |
12 | ![]() | MACNAMARA | ALP | 122.13 | 113.45 | 235.58 |
13 | ![]() | BENNELONG | LIBS | 166.74 | 65.35 | 232.09 |
14 | ![]() | KINGSFORD SMITH | ALP | 154.43 | 76.99 | 231.42 |
15 | ![]() | KOOYONG | LIBS | 128.25 | 88.15 | 216.39 |
16 | ![]() | BRISBANE | LNP | 119.08 | 95.41 | 214.50 |
17 | ![]() | MELBOURNE | GREENS | 111.10 | 99.33 | 210.43 |
18 | ![]() | COOK | LIBS | 158.02 | 51.78 | 209.80 |
19 | ![]() | BEROWRA | LIBS | 143.28 | 51.03 | 194.31 |
20 | ![]() | COOPER | ALP | 113.54 | 79.26 | 192.80 |
21 | ![]() | BONNER | LNP | 110.33 | 79.16 | 189.49 |
22 | ![]() | BOOTHBY | LIBS | 104.89 | 69.04 | 173.93 |
23 | ![]() | REID | LIBS | 127.86 | 42.69 | 170.55 |
24 | ![]() | MITCHELL | LIBS | 124.24 | 45.70 | 169.94 |
25 | ![]() | MONCRIEFF | LNP | 104.30 | 62.60 | 166.90 |
26 | ![]() | FAIRFAX | LNP | 101.14 | 63.77 | 164.91 |
27 | ![]() | MCPHERSON | LNP | 86.94 | 71.76 | 158.70 |
28 | ![]() | STIRLING | LIBS | 90.09 | 67.47 | 157.56 |
29 | ![]() | FREMANTLE | ALP | 90.46 | 65.08 | 155.55 |
30 | ![]() | CORANGAMITE | ALP | 87.38 | 63.72 | 151.10 |
31 | ![]() | FADDEN | LNP | 94.12 | 56.61 | 150.73 |
32 | ![]() | JAGAJAGA | ALP | 88.12 | 57.64 | 145.76 |
33 | ![]() | ISAACS | ALP | 97.70 | 47.10 | 144.80 |
34 | ![]() | FLINDERS | LIBS | 89.65 | 52.46 | 142.11 |
35 | ![]() | CHISHOLM | LIBS | 90.99 | 39.85 | 130.83 |
36 | ![]() | MENZIES | LIBS | 88.60 | 39.31 | 127.90 |
37 | ![]() | SWAN | LIBS | 68.60 | 57.27 | 125.87 |
38 | ![]() | CAPRICORNIA | LNP | 78.08 | 45.43 | 123.51 |
39 | ![]() | HUNTER | ALP | 90.61 | 32.48 | 123.10 |
40 | ![]() | DUNKLEY | ALP | 79.93 | 42.63 | 122.56 |
41 | ![]() | HINDMARSH | ALP | 73.80 | 48.72 | 122.51 |
42 | ![]() | CALARE | NATS | 89.37 | 29.12 | 118.49 |
43 | ![]() | FARRER | LIBS | 80.58 | 37.10 | 117.68 |
44 | ![]() | GRIFFITH | ALP | 63.52 | 53.43 | 116.95 |
45 | ![]() | BANKS | LIBS | 85.71 | 26.46 | 112.17 |
46 | ![]() | NEWCASTLE | ALP | 76.70 | 35.32 | 112.02 |
47 | ![]() | TANGNEY | LIBS | 55.33 | 53.35 | 108.69 |
48 | ![]() | MOORE | LIBS | 55.36 | 53.25 | 108.61 |
49 | ![]() | ROBERTSON | LIBS | 83.13 | 24.76 | 107.89 |
50 | ![]() | BALLARAT | ALP | 67.64 | 39.93 | 107.58 |
51 | ![]() | MAYO | CA | 61.98 | 39.12 | 101.10 |
52 | ![]() | GROOM | LNP | 61.45 | 39.36 | 100.80 |
53 | ![]() | BOWMAN | LNP | 63.34 | 36.37 | 99.70 |
54 | ![]() | MARIBYRNONG | ALP | 54.99 | 42.91 | 97.90 |
55 | ![]() | CASEY | LIBS | 56.14 | 40.37 | 96.52 |
56 | ![]() | FORREST | LIBS | 57.26 | 38.94 | 96.20 |
57 | ![]() | HUME | LIBS | 66.04 | 25.99 | 92.03 |
58 | ![]() | DEAKIN | LIBS | 65.70 | 25.97 | 91.67 |
59 | ![]() | DICKSON | LNP | 50.66 | 39.61 | 90.28 |
60 | ![]() | GRAYNDLER | ALP | 62.58 | 27.48 | 90.05 |
61 | ![]() | WHITLAM | ALP | 63.68 | 25.44 | 89.12 |
62 | ![]() | KENNEDY | KP | 57.91 | 30.59 | 88.50 |
63 | ![]() | RICHMOND | ALP | 51.84 | 36.04 | 87.88 |
64 | ![]() | BENDIGO | ALP | 58.28 | 29.27 | 87.55 |
65 | ![]() | BEAN | ALP | 55.60 | 31.61 | 87.21 |
66 | ![]() | BARKER | LIBS | 56.29 | 30.38 | 86.68 |
67 | ![]() | DURACK | LIBS | 57.92 | 27.42 | 85.34 |
68 | ![]() | LA TROBE | LIBS | 49.95 | 33.40 | 83.35 |
69 | ![]() | CANBERRA | ALP | 45.05 | 37.58 | 82.63 |
70 | ![]() | INDI | IND | 58.19 | 23.03 | 81.22 |
71 | ![]() | CLARK | IND | 55.79 | 24.72 | 80.51 |
72 | ![]() | FENNER | ALP | 53.49 | 25.63 | 79.11 |
73 | ![]() | BRUCE | ALP | 57.26 | 21.79 | 79.05 |
74 | ![]() | HASLUCK | LIBS | 46.33 | 31.34 | 77.68 |
75 | ![]() | SHORTLAND | ALP | 52.87 | 24.43 | 77.30 |
76 | ![]() | FLYNN | LNP | 54.24 | 22.59 | 76.83 |
77 | ![]() | STURT | LIBS | 41.81 | 33.18 | 74.99 |
78 | ![]() | MORETON | ALP | 41.97 | 31.90 | 73.87 |
79 | ![]() | CUNNINGHAM | ALP | 54.15 | 19.13 | 73.29 |
80 | ![]() | PARKES | NATS | 50.51 | 22.05 | 72.57 |
81 | ![]() | BARTON | ALP | 54.03 | 16.70 | 70.73 |
82 | ![]() | GELLIBRAND | ALP | 42.58 | 25.94 | 68.52 |
83 | ![]() | WIDE BAY | LNP | 46.87 | 21.49 | 68.36 |
84 | ![]() | O'CONNOR | LIBS | 51.20 | 16.98 | 68.18 |
85 | ![]() | COWAN | ALP | 42.21 | 25.17 | 67.39 |
86 | ![]() | BRAND | ALP | 38.91 | 28.45 | 67.36 |
87 | ![]() | GIPPSLAND | NATS | 48.74 | 17.34 | 66.08 |
88 | ![]() | EDEN-MONARO | ALP | 46.79 | 17.39 | 64.18 |
89 | ![]() | ASTON | LIBS | 43.50 | 19.18 | 62.68 |
90 | ![]() | CALWELL | ALP | 40.19 | 22.39 | 62.59 |
91 | ![]() | DAWSON | LNP | 38.94 | 23.05 | 61.99 |
92 | ![]() | COWPER | NATS | 48.33 | 13.47 | 61.79 |
93 | ![]() | PARRAMATTA | ALP | 47.12 | 14.42 | 61.54 |
94 | ![]() | OXLEY | ALP | 36.88 | 24.27 | 61.16 |
95 | ![]() | MALLEE | NATS | 44.57 | 15.44 | 60.01 |
96 | ![]() | LYNE | NATS | 46.26 | 13.50 | 59.76 |
97 | ![]() | PERTH | ALP | 31.62 | 27.80 | 59.41 |
98 | ![]() | HOTHAM | ALP | 36.61 | 21.88 | 58.49 |
99 | ![]() | GILMORE | ALP | 44.06 | 13.05 | 57.11 |
100 | ![]() | BURT | ALP | 30.90 | 25.69 | 56.58 |
101 | ![]() | NICHOLLS | NATS | 35.04 | 17.85 | 52.89 |
102 | ![]() | NEW ENGLAND | NATS | 39.93 | 12.96 | 52.89 |
103 | ![]() | WANNON | LIBS | 38.35 | 14.38 | 52.73 |
104 | ![]() | CORIO | ALP | 29.55 | 22.75 | 52.30 |
105 | ![]() | FOWLER | ALP | 39.71 | 11.68 | 51.39 |
106 | ![]() | LILLEY | ALP | 33.75 | 17.37 | 51.12 |
107 | ![]() | PATERSON | ALP | 38.81 | 12.04 | 50.85 |
108 | ![]() | PAGE | NATS | 35.14 | 15.16 | 50.30 |
109 | ![]() | FISHER | LNP | 33.39 | 15.90 | 49.29 |
110 | ![]() | GREY | LIBS | 32.51 | 16.66 | 49.17 |
111 | ![]() | LINDSAY | LIBS | 36.39 | 11.71 | 48.11 |
112 | ![]() | SOLOMON | ALP | 34.30 | 13.75 | 48.04 |
113 | ![]() | PEARCE | LIBS | 27.34 | 18.71 | 46.06 |
114 | ![]() | MCEWEN | ALP | 30.73 | 15.10 | 45.83 |
115 | ![]() | MACQUARIE | ALP | 34.85 | 10.34 | 45.19 |
116 | ![]() | MARANOA | LNP | 26.38 | 18.02 | 44.40 |
117 | ![]() | BLAIR | ALP | 27.16 | 15.94 | 43.10 |
118 | ![]() | LONGMAN | LNP | 28.65 | 14.43 | 43.09 |
119 | ![]() | BASS | LIBS | 27.10 | 15.90 | 43.00 |
120 | ![]() | DOBELL | ALP | 31.89 | 10.23 | 42.12 |
121 | ![]() | MONASH | LIBS | 28.58 | 13.38 | 41.96 |
122 | ![]() | FRANKLIN | ALP | 25.92 | 15.12 | 41.04 |
123 | ![]() | HUGHES | LIBS | 28.28 | 11.23 | 39.51 |
124 | ![]() | GREENWAY | ALP | 27.64 | 11.33 | 38.96 |
125 | ![]() | BRADDON | LIBS | 21.90 | 15.20 | 37.10 |
126 | ![]() | RANKIN | ALP | 21.86 | 15.18 | 37.04 |
127 | ![]() | FRASER | ALP | 24.97 | 11.62 | 36.60 |
128 | ![]() | PETRIE | LNP | 19.89 | 15.11 | 35.00 |
129 | ![]() | WILLS | ALP | 21.84 | 12.94 | 34.77 |
130 | ![]() | BLAXLAND | ALP | 28.86 | 5.79 | 34.65 |
131 | ![]() | HOLT | ALP | 23.99 | 9.78 | 33.76 |
132 | ![]() | LALOR | ALP | 19.66 | 12.34 | 32.00 |
133 | ![]() | LEICHHARDT | LNP | 21.98 | 9.97 | 31.94 |
134 | ![]() | MAKIN | ALP | 20.79 | 11.11 | 31.90 |
135 | ![]() | LINGIARI | ALP | 21.46 | 9.66 | 31.12 |
136 | ![]() | CANNING | LIBS | 17.41 | 12.90 | 30.31 |
137 | ![]() | FORDE | LNP | 16.92 | 11.98 | 28.90 |
138 | ![]() | HINKLER | LNP | 21.37 | 5.90 | 27.27 |
139 | ![]() | RIVERINA | NATS | 18.79 | 7.93 | 26.73 |
140 | ![]() | SCULLIN | ALP | 17.01 | 8.77 | 25.78 |
141 | ![]() | HERBERT | LNP | 15.35 | 10.17 | 25.51 |
142 | ![]() | WRIGHT | LNP | 15.35 | 9.45 | 24.80 |
143 | ![]() | GORTON | ALP | 18.79 | 5.56 | 24.34 |
144 | ![]() | SPENCE | ALP | 15.42 | 6.22 | 21.64 |
145 | ![]() | MCMAHON | ALP | 16.80 | 4.36 | 21.16 |
146 | ![]() | LYONS | ALP | 14.16 | 5.60 | 19.76 |
147 | ![]() | CHIFLEY | ALP | 16.68 | 2.70 | 19.38 |
148 | ![]() | MACARTHUR | ALP | 13.49 | 5.35 | 18.84 |
149 | ![]() | KINGSTON | ALP | 10.53 | 5.05 | 15.58 |
150 | ![]() | WATSON | ALP | 11.35 | 2.64 | 13.99 |
151 | ![]() | WERRIWA | ALP | 8.23 | 2.12 | 10.35 |
Click on the MP to display Commonwealth grants data for that electorate including:
Click on the MP to display ACNC charities & demographic data for that electorate including:
Click on the MP to display AEC data for that electorate including:
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This new project geocodes data to let you see important information for your local area by electorate, directing you to the decision maker to lobby for each dataset. You can see all electorates at once on page load or you can click the geolocation button to let the browser focus on your local area. Franking credits near me displays tax data for a range of variables including totaling franking credits received by individuals and from shares and partnerships. Grants near me shows Commonwealth grants by electorate. Click on the electorate link through to the grants project to see much more detail on each electorate from the grants project. Charites near me provides aggregated financial data from charities by electorate. Click through to the charities project updated welfare recipient numbers including both JobSeeker and JobKeeper by electorate with charity financial data aggregated by electorate to allow charities, advocates and decision makers to see the financial health of charities in each electorate and the number of welfare recipients they may be dealing with as a result of Covid-19. Influencers near me provides payments to political parties (including non-donations) by area. You can see who has made payments to parties near you and click through to the donations project to map by donor, category (eg business, individual, trusts & estates etc). |
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Whether a donor is an individual or an organisation, I take privacy issues seriously. For this reason unless I am given specific instructions about who a donor is and that you are happy for me to share publicly that you are a patron of my work I do not thank individual donors publicly.
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Bill McLennan |
FORMER HEAD, AUSTRALIAN BUREAU OF STATISTICS |
I was impressed by the #Censusfail submission to this (Inquiry) Committee. It very clearly showed some good analysis that would have helped the ABS to run a better Census if it had done such research before developing the Census proposal. It also saved me from explaining the current thrust in government with the Government Data Linkage Project, and its likely links to the Census. Bill McLennan (Former Head of the ABS, Former Chairman United Nations Statistical Commission) in his Submission to the 2016 Inquiry. |
Garry Brooke |
FORMER DIRECTOR, APPROPRIATIONS MANAGEMENT TEAM, DEPARTMENT OF FINANCE |
Iβve worked with Rosie Williams on budget data transparency since November 2013. Rosie has developed her project into the best government data transparency initiative I know... continually updated and improved to make underlying data intelligible and to focus on key aspects for analysis. My interest has particularly been on the transparency of federal budget data. |
Scott Ludlam |
FORMER SENATOR, THE AUSTRALIAN GREENS |
We could hear from digital rights organisations like the Privacy Foundation, Digital Rights Watch and Electronic Frontiers Australia and from specialist researchers like Rosie Williams and Asher Wolf, who have led the debate online. (Australian Hansard) |
Sleeping Giants | |
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A COMMUNITY INITIATIVE TO MAKE RACISM, BIGOTRY, MISOGYNY & CLIMATE CHANGE DENIAL LESS PROFITABLE In late 2018, Sleeping Giants Australia, 'a community initiative to make racism, bigotry, misogyny and climate change denial less profitable', used data I provided to them on the parliamentarians who have accepted subscriptions to Foxtel in their campaign against racism. Sky took umbridge at this campaign and Sleeping Giants & similar campaigns have been the focus of media commentary ever since. My Tweet was pictured in a front-page diatribe in The Australian against Denise Shrivell who The Australian claimed is resonsible for the Sleeping Giants Australia account. |
I launched the domain AusGov.info at Linux Conference Australia in January 2018, however this work is the result of years devoted to programming and transparency work beginning in 2012 and progressively expanded and improved upon over the intervening years.
The NSW Ministerial Diaries data (not currently online) was supplied by Nick Evershed and associates. The pecuniary interests register data was originally supplied by icacpls however for over a year I have updated it manually.
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The figures in this site are either raw data at line-item level or totals/percentages - which are the result of algorithms or joins (programmatic matches between two lists) - written by myself in MySQL, which in turn are based on open data provided by Australian government agencies.
This data ranges in quality between datasets, is updated at different intervals and is published to different standards and in different formats.
The data you see in this site is edited by myself (unused fields are removed, names of programs/agencies/entities are spelled consistently within & between datasets). Data cleaning is a significant job. Data schemas & other information is available here. Click on the dataset icons.
All care has been taken to represent every single figure accurately, however mistakes can be made either by the entity providing data to the government, the agency providing the data back to the public or at my end as I further transform this data for use.
It is important to understand that while opinions and inferences can be made based on the data on this site, that the data is not in and of itself an inference or an opinion. Inferences and opinions using data in this site remain the legal responsibility of the author of those opinions.
If I share these opinions/inferences in a tweet this does not imply that this is my opinion but that I am sharing the opinion of another person for comment.
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