Medals per Million

Update: as for 16 August 2016, Data from BBC, rio2016.com and Wikipedia:

17 August Medals metrics by GDP

Rank

Country

Gold

Silver

Bronze

Total

Popula–tion (M)

Medals per Million

Golds per Million

Medals per GDP $m

61 GRN

0

1

0

1

0.1

9.71

0.00

1000.00

36 ARM

1

3

0

4

3.0

1.34

0.33

371.26

40 GEO

1

1

3

5

3.7

1.34

0.27

358.63

19 JAM

3

0

2

5

2.7

1.84

1.10

355.69

48 FIJ

1

0

0

1

0.9

1.15

1.15

201.45

59 MGL

0

1

1

2

3.1

0.65

0.00

171.64

69 KGZ

0

0

1

1

6.0

0.17

0.00

165.84

69 MDA

0

0

1

1

3.6

0.28

0.00

164.37

22 CUB

2

2

4

8

11.2

0.71

0.18

160.23

48 KOS

1

0

0

1

1.8

0.54

0.54

154.54

54 AZE

0

2

3

5

9.8

0.51

0.00

142.28

48 BAH

1

0

0

1

0.4

2.65

2.65

112.15

12 HUN

6

3

4

13

9.8

1.32

0.61

110.42

37 BLR

1

2

2

5

9.5

0.53

0.11

108.96

18 CRO

3

2

0

5

4.2

1.19

0.72

100.14

30 UZB

2

0

4

6

31.6

0.19

0.06

97.33

16 KEN

3

3

0

6

44.2

0.14

0.07

92.75

38 SLO

1

2

1

4

2.1

1.94

0.48

91.34

20 KAZ

2

3

5

10

17.8

0.56

0.11

86.09

33 UKR

1

4

2

7

42.7

0.16

0.02

83.78

40 ETH

1

1

3

5

92.2

0.05

0.01

74.15

58 LTU

0

1

2

3

2.9

1.05

0.00

69.73

48 SER

1

0

0

1

14.8

0.07

0.07

68.62

43 BHR

1

1

0

2

1.4

1.42

0.71

66.49

14 NZ

3

6

1

10

4.7

2.12

0.64

58.85

69 EST

0

0

1

1

1.3

0.76

0.00

41.93

39 CZE

1

1

5

7

10.6

0.66

0.09

37.78

4 RUS

12

12

14

38

146.6

0.26

0.08

33.55

35 DEN

1

3

5

9

5.7

1.57

0.17

29.82

32 SA

1

5

1

7

55.7

0.13

0.02

26.29

69 TUN

0

0

1

1

11.2

0.09

0.00

22.73

43 SVK

1

1

0

2

5.4

0.37

0.18

22.27

42 ROM

1

1

2

4

19.9

0.20

0.05

21.98

27 GRE

2

1

1

4

10.9

0.37

0.18

20.56

9 AUS

7

8

9

24

24.2

0.99

0.29

19.99

7 NED

8

3

3

14

17.0

0.82

0.47

18.36

2 GB

19

19

12

50

65.1

0.77

0.29

18.11

24 COL

2

2

0

4

48.8

0.08

0.04

15.80

23 POL

2

2

3

7

38.4

0.18

0.05

14.78

21 PRK

2

3

2

7

25.3

0.28

0.08

13.01

6 ITA

8

9

6

23

60.7

0.38

0.13

12.44

8 FRA

7

11

11

29

66.7

0.43

0.10

11.77

34 SWE

1

4

1

6

9.9

0.61

0.10

11.70

25 BEL

2

1

2

5

11.3

0.44

0.18

10.75

11 KOR

6

3

5

14

50.8

0.28

0.12

10.60

31 IRN

2

0

2

4

79.5

0.05

0.03

10.36

48 PUR

1

0

0

1

10.3

0.10

0.10

10.03

43 VIE

1

1

0

2

92.7

0.02

0.01

9.93

27 THA

2

1

1

4

65.7

0.06

0.03

9.76

17 CAN

3

2

9

14

36.2

0.39

0.08

9.57

69 MOR

0

0

1

1

34.0

0.03

0.00

9.25

66 NOR

0

0

3

3

5.2

0.57

0.00

8.18

56 IRE

0

2

0

2

4.8

0.42

0.00

7.86

25 SWI

2

1

2

5

8.3

0.60

0.24

7.67

5 GER

11

8

7

26

81.8

0.32

0.13

7.50

15 BRZ

3

4

4

11

206.5

0.05

0.01

7.17

29 ARG

2

1

0

3

43.6

0.07

0.05

6.85

10 JPN

7

4

18

29

127.0

0.23

0.06

6.57

67 ISR

0

0

2

2

8.5

0.23

0.00

6.53

59 MAS

0

1

1

2

31.0

0.06

0.00

6.47

67 EGY

0

0

2

2

91.5

0.02

0.00

6.05

61 ALG

0

1

0

1

40.4

0.02

0.00

6.03

46 TPE

1

0

2

3

23.5

0.13

0.04

5.90

61 QAT

0

1

0

1

2.3

0.43

0.00

5.85

13 SPA

4

1

2

7

46.4

0.15

0.09

5.63

61 VEN

0

1

0

1

31.0

0.03

0.00

5.39

69 POR

0

0

1

1

10.3

0.10

0.00

4.88

1 US

28

28

28

84

324.2

0.26

0.09

4.53

3 CHN

17

15

19

51

1378.2

0.04

0.01

4.48

55 TUR

0

2

1

3

78.7

0.04

0.00

3.99

48 SIN

1

0

0

1

5.5

0.18

0.18

3.39

61 PHI

0

1

0

1

102.9

0.01

0.00

3.22

69 UAE

0

0

1

1

9.9

0.10

0.00

3.08

69 AUT

0

0

1

1

8.7

0.11

0.00

2.60

56 IDN

0

2

0

2

258.7

0.01

0.00

2.13

47 IOA

1

0

1

2

0.0

Yes, of course USA is top nation at the moment (in terms of Olympic medals) but it’s got a large population. Wouldn’t a fairer comparison be medals per head of population, or rather, per million. Here are the results sorted that way, as of 15 August 2016:

medals per head of population smaller Medals Per Million 15 August

David with Ashe team

It sounds odd when you put it like that… but actually it’s just how we say it

I spent the last week working with the Koro Ashe Translation team again. They are based 3 hours to the west but we worked this week in Jos. (If you receive news and prayer requests from Wycliffe.org.uk you might have heard mention of them as they are supported in particular by some British churches.)

IMG_1764

Some more interesting features of Ashe language came out in Luke 12, where Jesus says he has come not to bring peace but division. ‘Peace’ is expressed as ‘lying heart’ (that is, ‘restful mind’) which had me rather puzzled until it was explained. And where I was expecting a mother-in-law to pop up divided against her daughter-in-law, we ended up with ‘grandmother’. Ashe uses ingkoko ‘grandmother’ and then wife-of-her-son in this situation. That is one of those situations where it sounds odd in English, but everything is OK as far as the Ashe translation is concerned; they had done their job well. Merely translating the 3 English words ‘mother-in-law’ piece-by-piece would have been perplexing and meaningless and also not faithful to the original Greek.

Unexpectedly familiar: ‘Bean pods’ of Luke 15

Last week I made a discovery that surprised both me and the translation team I was working with: that the ‘bean pods’ the young prodigal of Luke 15 wanted to ‘fill himself with’ neither the generic food scraps we might think, or the sloppy grain-husk-porridge people feed pigs with here but were the fruit of a tree very familiar to us in West Africa.

To be fair we are not the first people to have made this discovery since the information was sitting in dictionaries and translators’ helps waiting to be uncovered, but the fact is we were all so sure we understood what the boy fed the pigs that we didn’t even consider it might be wrong. Continue reading Unexpectedly familiar: ‘Bean pods’ of Luke 15

A basket of about 100 large unripe mangos from the fallen branch

Premature Mango Harvest

One morning there was suddenly a huge crashing noise just outside the homeschool room; one of our mango trees had over-reached itself in enthusiasm for producing hefty fruit and a large branch crashed to the ground. Green, unripe (but rather large) mangos were scattered all over the place. We picked up a massive basket load which provided a great opportunity for practising estimation. Around 100 mangos were then cooked into a very convincing “apple sauce” to the surprise and interest of our gardener Samuel who had never considered cooking mangos, let alone unripe ones.

Fallen branch from our mango tree
Fallen branch from our mango tree
A basket of about 100 large unripe mangos from the fallen branch
A basket of about 100 large unripe mangos from the fallen branch

Is translation easy or impossible?

For centuries – probably millenia – people have argued about whether translation is actually possible, whilst doing it and relying on it all the time. Some treat it as a mechanical – obvious – process, just switching words around. But most people who have been involved in meaningful translation realise that it’s a lot harder than that. So what perspective is true?

It’s occurred to me, as someone who struggles with learning languages, that translation maybe is only as hard as learning a language well. What do you think?

That means it’s tough, but not impossible. The hardest bit is probably learning to discard the assumptions and patterns from language A when learning and using language B.

Homeschool resuming

OLYMPUS DIGITAL CAMERA
Tea break in our school room

Homeschool started again for Rebekah and Elizabeth a few days after we arrived back in Nigeria. Rebekah was back to her familiar pink desk, and Elizabeth chose purple for an identical desk that our carpenter Weze made for her. Abigail is keen not to be left out, but she also lost no time in forming a strong friendship with 2 year-old David who moved to next door while we were away in the UK. Auntie Sarah has been helping to look after Helen while working on the morning chores so that Julie has a bit of peace to teach the big girls. They’ve been getting going by 8 and finishing up around noon.