እ ᅜ ㄒ䠄 ⱥ ㄒ䠅

(1)

௧ ࿴ 䠏 ᖺ ᗘ

୍ ⯡ ධ Ꮫ ヨ㦂䠄 ๓ ᮇ 䐟䠅 ၥ 㢟

እ ᅜ ㄒ䠄 ⱥ ㄒ䠅

( ⸆ Ꮫ 㒊 ࣭ ┳ ㆤ Ꮫ 㒊 ࣭ ೺ ᗣ ་ ⒪ ⛉ Ꮫ 㒊 ࣭ ᚰ ⌮ Ꮫ 㒊 ࣭ ᅜ 㝿 ┳ ㆤ Ꮫ 㒊 )

ὀ ព ஦ 㡯

1. ၥ㢟෉Ꮚ䛿䠈ヨ㦂┘╩⪅䛾ᣦ♧䛜䛒䜛䜎䛷㛤䛔䛶䛿䛔䛡䜎䛫䜣䚹

2. ၥ㢟෉Ꮚ䛸ゎ⟅⏝⣬䠄䝬䞊䜽䝅䞊䝖䠅䛿ู䛻䛺䛳䛶䛔䜎䛩䚹

3. ゎ⟅⏝⣬䛻䛿ゎ⟅ḍ௨እ䛻ୗグ䐟䡚䐢䛾グධḍ䛜䛒䜛䛾䛷䠈┘╩⪅䛾 ᣦ♧䛻ᚑ䛳䛶䛭䜜䛮䜜ṇ䛧䛟グධ䛧䠈䝬䞊䜽䛧䛺䛥䛔䚹

䐟 Ặྡḍ Ặྡ䛚䜘䜃䝣䝸䜺䝘䜢グධ䛧䛺䛥䛔䚹

䐠 ཷ㦂␒ྕḍ ཷ㦂␒ྕ䠄ᩘᏐ䛚䜘䜃ⱥᏐ䠅䜢グධ䛧䠈䛥䜙䛻䛭䛾ୗ䛾䝬䞊䜽ḍ䛻䝬䞊䜽䛧䛺䛥䛔䚹

䐡ヨ㦂✀ูḍ 䛆୍⯡๓ᮇ1᪥┠䛇䛻䝬䞊䜽䛧䛺䛥䛔䚹䐢 ᩍ⛉䞉⛉┠ḍ 䛆እᅜㄒ䠄ⱥㄒ䠅䛇䛻䝬䞊䜽䛧䛺䛥䛔䚹

4. ゎ⟅䛿䠈ゎ⟅⏝⣬䛾ゎ⟅ḍ䛻䝬䞊䜽䛧䛺䛥䛔䚹

౛䛘䜀䠈 10 䛸⾲♧䛾䛒䜛ၥ䛔䛻ᑐ䛧䛶䐡䛸ゎ⟅䛩䜛ሙྜ䛿䠈

ḟ䛾 [౛] 䛾䜘䛖䛻ゎ⟅␒ྕ10䛾ゎ⟅ḍ䛾䐡䛻䝬䞊䜽䛧䛺䛥䛔䚹

[౛] ゎ⟅

␒ྕ

ゎ ⟅ ḍ

1 2 3 4 5 6 7 8 9 0

10 䐟䐠䖃䐢䐣䐤䐥䐦䐧䒩

5. ヨ㦂᫬㛫䛿䠈60ศ䛷䛩䚹

(2)

(3)

䊠 ḟ䛾ⱥᩥ䜢ㄞ䜣䛷タၥ䛻⟅䛘䜘䚹

It was October 1995 and little did I know that after my class that evening, I was going to start my lifelong fight against global misconceptions.

“What is the child ( 1 ) in Saudi Arabia? Don’t raise your hands. Just shout it out.” I had handed out copies of tables 1 and 5 from UNICEF’s yearbook. The handouts looked dull, but I was excited.

A choir of students shouted in unison: “THIRTY-FIVE.”

“Yes. Thirty-five. Correct. This means that 35 children die before their fifth birthday out of every thousand live births. Give me the number now for Malaysia?”

“FOURTEEN,” came the chorus.

As the numbers were thrown back at me, I scribbled them with a green pen onto a plastic film on the overhead projector.

“Fourteen,” I repeated. “Fewer than Saudi Arabia!”

My *dyslexia played a little trick on me and I wrote “Malaisya.” The students laughed.

“Brazil?”

“FIFTY-FIVE.”

“Tanzania?”

“ONE HUNDRED AND SEVENTY-ONE.”

I put the pen down and said, “Do you know why I’m obsessed with the numbers for the child ( 1 )? It’s not only that I care about children. This measure takes the temperature of a whole society. Like a huge thermometer. Because children are very fragile. There are so many things that can kill them. When only 14 children die out of 1,000 in Malaysia, this means that ( 2 ) 986 survive. Their parents and their society manage to protect them from all the dangers that could have killed them: germs, starvation, violence, and so on. So this number 14 tells us that most families in Malaysia have enough food, their sewage systems don’t leak into their drinking water, they have good access to primary health care, and mothers can read and write. It doesn’t just tell us about the health of children.

(3) It measures the quality of the whole society.

“It’s not the numbers that are interesting. It’s what ⁽⁴⁾about / us / tell / the / they / lives behind the numbers,” I continued. “Look how different these numbers are: 14, 35, 55, and 171. Life in these countries must be extremely different.”

I picked up the pen. “Tell me now how life was in Saudi Arabia 35 years ago?

How many children died in 1960? Look in the second column.”

“TWO HUNDRED … and forty two.”

The volume dropped as my students articulated the big number: 242.

この部分に記載されている文章については、

著作権上の問題から公表することができません。

(4)

“Yes. That’s correct. Saudi Arabian society has made amazing progress, hasn’t it? Child deaths per thousand dropped from 242 to 35 in just 33 years. That’s way faster than Sweden. We took 77 years to achieve the same improvement.

“What about Malaysia? Fourteen today. What was it in 1960?”

“Ninety-three,” came the mumbled response. The students had all started searching through their tables, puzzled and confused. A year earlier, I had given my students the same examples, but with no data tables to back them up, and they had simply refused to believe what I told them about the improvements across the world. Now, with all the evidence right in front of them, this year’s students were instead rolling their eyes up and down the columns, to see if I had picked exceptional countries and tried to cheat them. They couldn’t believe the picture they saw in the data. It didn’t look anything like the picture of the world they had in their heads.

“Just so you know,” I said, “you won’t find any countries ( 5 ) child mortality has increased. Because the world in general is ( 6 ). Let’s have a short coffee break.”

䠄ὀ䠅 *dyslexia^:ኻㄞ⑕䠈ㄞ䜏᭩䛝㞀ᐖ

(5)

ၥ㸯 ᩥ୰䛻2䛴䛒䜛✵ᡤ ( ¹ ⁾ 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 1 䐟 survival rate

䐠 death number 䐡 mortality rate 䐢 personality number

ၥ㸰 ✵ᡤ ( ² ⁾ 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 2

䐟 other 䐠 the other 䐡 more than 䐢 some other

ၥ㸱 ୗ⥺㒊 (3) 䛜♧䛩䜒䛾䛸䛧䛶᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 3

䐟 this number 14 䐠 enough food

䐡 good access to primary health care 䐢 the health of children

ၥ㸲 ୗ⥺㒊 (4) 䜢ព࿡䛜㏻䜛䜘䛖䛻୪䜉᭰䛘䛯䛸䛝䠈䠎␒┠䛸䠑␒┠䛻᮶䜛⤌ྜ䛫䛿ḟ䛾䛖䛱䛹䜜䛛䚹 4

䐟䠎␒┠䠖 lives ^䠑␒┠䠖 us 䐠䠎␒┠䠖 tell ^䠑␒┠䠖 the 䐡䠎␒┠䠖 they ^䠑␒┠䠖 about 䐢䠎␒┠䠖 the ^䠑␒┠䠖 tell

ၥ㸳 ✵ᡤ ( ⁵ ⁾ 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 5

䐟 which 䐠 what 䐡 where 䐢 that

ၥ㸴 ✵ᡤ ( ⁶ ⁾ 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 6

䐟 becoming worse 䐠 a place hard to live in 䐡 getting better

䐢 a dangerous place

(6)

䊡 ḟ䛾ⱥᩥ䛸䜾䝷䝣䜢ㄞ䜣䛷タၥ䛻⟅䛘䜘䚹

Governments need to raise *¹carbon prices much faster if they are to meet their commitments on ( 1 ) emissions and ( 2 ) the pace of climate change under

*²the Paris Agreement, according to a new OECD report.

Effective Carbon Rates 2018: Pricing Carbon Emissions through Taxes and Emissions Trading presents new data on taxes and tradeable permits for carbon emissions in 42 OECD and G20 countries accounting for around 80% of global emissions. It finds that today’s carbon prices – while slowly rising – are still too low to have a significant impact on curbing climate change.

The report shows that ⁽³⁾the carbon pricing gap – which compares actual carbon prices and real climate costs, estimated at EUR 30 per tonne of CO2 – was 76.5%

in 2018. This compares favourably with the 83% carbon gap reported in 2012 and the 79.5% gap in 2015, but it is still insufficient. At the current pace of decline, carbon prices will only meet real costs in 2095. Much faster action is needed to incentivise companies to innovate and compete to bring about a low-carbon economy and to stimulate households to adopt low-carbon lifestyles.

“The gulf between today’s carbon prices and the actual cost of emissions to our planet is unacceptable,” said OECD Secretary-General Angel Gurría. “Pricing carbon correctly is a concrete and cost-effective way to slow climate change. We are wasting an opportunity to steer our economies along a low-carbon growth path and losing precious time with every day that passes.”

The report measures carbon prices using ⁽⁴⁾the Effective Carbon Rate, which is the sum of three components: specific taxes on fossil fuels, carbon taxes and prices of tradeable emission permits. All three instruments increase the price of high-carbon relative to low- and zero-carbon fuels, encouraging energy users to go for low- or zero-carbon options.

The vast majority of emissions in industry and in the residential and commercial sector are entirely unpriced, the report finds. The carbon pricing gap is lowest for road transport (21% against the EUR 30 benchmark) and highest for industry (91%). The gap is over 80% in the electricity and the residential and commercial sectors.

(7)

Country analysis on 2015 carbon prices shows large variations, with carbon pricing gaps ranging from as low as ( 5 ) in Switzerland to above 90% in some emerging economies. France, India, Korea, Mexico and the United Kingdom substantially reduced their carbon pricing gaps between 2012 and 2015. Yet, still only 12 of the 42 countries studied had pricing gaps of below 50% in 2015.

New carbon pricing initiatives in some countries, such as China’s emissions trading scheme and renewed efforts in Canada and France to price carbon, could significantly reduce these gaps. The carbon-intensity of GDP is usually lower in countries with lower carbon pricing gaps.

The report rates emission trading as an effective way to price emissions,

(6) providing permit prices are stable at realistically high levels. Taxes have the advantage of simple administration, especially if grafted onto existing tax regimes. Revenue-neutral reforms can enable other taxes to be cut or carbon pricing can facilitate domestic revenue mobilisation.

䠄ὀ䠅 *¹carbonprices^:^Ⅳ⣲౯᱁ *²theParisAgreement^:^䝟䝸༠ᐃ

0 10 20 30 40 50 60 70 80 90

SwitherlandFrance United KingdomGermanyAustraliaCanadaJapanItaly

The carbon pricing gap varies widely by country

Carbon pricing gap in 2015, in %

(8)

ၥ㸯 ✵ᡤ ( 1 ) 䛸 ( 2 ) 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺⤌ྜ䛫䛿ḟ䛾䛖䛱䛹䜜䛛䚹 7

䐟 ( ¹ ⁾^䠖 cutting ⁽ ² ⁾^䠖 slowing 䐠 ( ¹ ⁾^䠖 decreasing ⁽ ² ⁾^䠖 quickening 䐡 ( ¹ ⁾^䠖 increasing ⁽ ² ⁾^䠖 preventing 䐢 ( ¹ ⁾^䠖 producing ⁽ ² ⁾^䠖 keeping

ၥ㸰 ୗ⥺㒊 (3) 䛾ㄝ᫂䛸䛧䛶᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 8 䐟 ஧㓟໬Ⅳ⣲1䝖䞁ᙜ䛯䜚30䝴䞊䝻䛷⟬ฟ䛧䛯䛸䛝䛾Ⅳ⣲౯᱁ 䐠䝶䞊䝻䝑䝟䛻䛚䛡䜛1ᖺ㛫䛾஧㓟໬Ⅳ⣲᤼ฟ㔞䛾ྜィ

䐡 ᐇ㝿䛾Ⅳ⣲౯᱁䛸ᐇ㉁ⓗ䛺Ẽೃኚື䛾䝁䝇䝖䛸䜢ẚ㍑䛧䛯᱁ᕪ 䐢 Ⅳ⣲᤼ฟ㔞䛸䛭䜜䛻䛸䜒䛺䛖Ẽೃኚື䛾ᐇ㉁ⓗ䛺๭ྜ

ၥ㸱 ୗ⥺㒊 (4) 䛾ㄝ᫂䛸䛧䛶᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 9

䐟 ໬▼⇞ᩱ⛯䠈Ⅳ⣲⛯䠈᤼ฟᶒྲྀᘬ౯᱁䛜඲య䛻༨䜑䜛ẚ⋡

䐠 ໬▼⇞ᩱ⛯䠈Ⅳ⣲⛯䠈᤼ฟᶒྲྀᘬ౯᱁䜢ྜィ䛧䛯್ẁ 䐡 ໬▼⇞ᩱ⛯䠈Ⅳ⣲⛯䠈᤼ฟᶒྲྀᘬ౯᱁䛭䜜䛮䜜䛾ኚ໬㏿ᗘ 䐢 ໬▼⇞ᩱ⛯䠈Ⅳ⣲⛯䠈᤼ฟᶒྲྀᘬ౯᱁䛸䛔䛖3䛴䛾せ⣲

ၥ㸲 ✵ᡤ ( 5 ) 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 10

䐟 17%

䐠 22%

䐡 27%

䐢 32%

ၥ㸳 ୗ⥺㒊 (6) 䜢௚䛾⾲⌧䛻⨨䛝᥮䛘䜛䛸䛝䠈᭱䜒㐺ᙜ䛺䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 11

䐟 giving 䐠 as soon as 䐡 without 䐢 as long as

ၥ㸴 ᮏᩥ䛺䜙䜃䛻䜾䝷䝣䛾ෆᐜ䛻ྜ䛖䜒䛾䛿ḟ䛾䛖䛱䛹䜜䛛䚹 12

䐟 ᐙィ䛻ᑐ䛧䛶పⅣ⣲䛾⏕ά䝇䝍䜲䝹䜢ồ䜑䜛䛣䛸䛿ᛴ䛜䛺䛔䚹䐠 ᪥ᮏ䛿ẚ㍑ⓗ㐺ṇ䛺Ⅳ⣲౯᱁䜢䛴䛡䛶䛔䜛䛸ゝ䛘䜛䚹

䐡 ၟᴗ㒊㛛䛛䜙䛾᤼ฟ㔞䛾኱༙䛻䛿Ⅳ⣲౯᱁䛜඲䛟䛴䛡䜙䜜䛶䛔䛺䛔䚹䐢 ୰ᅜ䛾᤼ฟᶒྲྀᘬไᗘ䛷䛿䜋䛸䜣䛹䛭䛾ຠᯝ䛿ぢ㎸䜑䛺䛔䚹

(9)

䊢 ḟ䛾ྛၥ䛔䠄 ၥ㸯䡚ၥ 10 䠅䛾✵ᡤ䜢⿵䛖䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䜢䠈䛭䜜䛮䜜ୗ䛾䐟䡚䐢䛛䜙୍䛴䛪䛴㑅䜉䚹

ၥ㸯 Bob 13 because the train didn’t come on time^.

䐟 was annoying 䐠 annoyed 䐡 had been annoyed 䐢 got annoyed

ၥ㸰 Janet was afraid that her sister’s advice would not 14 any difference^. 䐟 make 䐠 take 䐡 change 䐢 tell

ၥ㸱 You should keep the cheese on the pizza 15 burning^. 䐟 for 䐠 against 䐡 from 䐢 at

ၥ㸲 New school buildings 16 constructed on campus now^. 䐟 have 䐠 were 䐡 are being 䐢 had been

ၥ㸳 Steve has 17 some money from his brother to go to the rock festival^. 䐟 lent 䐠 borrowed 䐡 sold 䐢 bought

ၥ㸴 In America^, my host mother treated me as if I 18 her own son^. 䐟 am 䐠 were 䐡 have been 䐢 look like

ၥ㸵 The manager got them 19 the whole floor thoroughly after closing the restaurant^.

䐟 clean 䐠 cleaned 䐡 to clean 䐢 be cleaning

ၥ㸶 Running out of time^, the candidate had to 20 her speech by about five minutes^.

䐟 short 䐠 shorter 䐡 shortage 䐢 shorten

ၥ㸷 The price of the sport car is much higher 21 .

䐟 than the family cars 䐠 than that of the family car 䐡 as family cars 䐢 than one of the family cars

ၥ10 My grandfather doesn’t remember 22 the letter by himself last week^. 䐟 to post 䐠 posted 䐡 to have posted 䐢 posting

(10)

䊣 ḟ䛾ྛၥ䛔䠄ၥ㸯䡚ၥ㸳䠅䛻䛚䛔䛶䠈䛭䜜䛮䜜ୗ䛾䐟䡚䐣䛾ㄒྃ䜢୪䜉᭰䛘䛶✵ᡤ䜢⿵䛔䠈ᩥ

䜢᏶ᡂ䛥䛫䜘䚹䛯䛰䛧䠈ゎ⟅䛿 23 䡚 32 䛻ධ䜜䜛䜒䛾䛾␒ྕ䛾䜏䜢⟅䛘䜘䚹

ၥ㸯䝡䝸䞊䛿䝟䞊䝔䜱䞊䛷䛭䛾⏨䜢ぢ䛯䛸☜ಙ䛧䛶䛔䛯䚹

Billy 23 24 the man at the party^. 䐟 of 䐠 seen 䐡 certain 䐢 was 䐣 having

ၥ㸰 ᙼዪ䛜᫖᪥ᫎ⏬䛻⾜䛡䛺䛛䛳䛯䛾䛿⑓Ẽ䛷ᐷ㎸䜣䛷䛔䛯䛛䜙䛰䚹

It 25 26 in bed that she couldn’t go to the movies yesterday^.

䐟 was 䐠 is 䐡 because 䐢 sick 䐣 she

ၥ㸱 ᫨䛻䛯䛟䛥䜣㣗䜉䛯䛾䛷䠈௒䛿ኤ㣗䜢㣗䜉䜛Ẽ䛜䛧䛺䛔䚹

Having eaten a big lunch^, I 27 28 now^. 䐟 eating 䐠 like 䐡 dinner 䐢 feel 䐣 don’t

ၥ㸲 ⓙ䛣䛾⾤䜢㞳䜜䛶䛧䜎䛳䛯䛜䠈䛚஫䛔䛻㐃⤡䜢ྲྀ䜚⥆䛡䛶䛔䜛䚹

Although they all have left this town^, they have 29 30 another^.

䐟 touch 䐠 one 䐡 with 䐢 in 䐣 kept

ၥ㸳 ∗䛿⭎䜢⤌䜣䛷⚾䛾ヰ䜢⫈䛔䛶䛔䛯䚹

My father listened to 31 32 ^.

䐟 crossed 䐠 me 䐡 his 䐢 with 䐣 arms

(11)

䊤 ḟ䛾ᑐヰᩥ䛾 33 䡚 37 䛻ධ䜜䜛䛾䛻᭱䜒㐺ᙜ䛺䜒䛾䜢䠈䛭䜜䛮䜜ୗ䛾䐟䡚䐢䛛䜙୍

䛴䛪䛴㑅䜉䚹

ၥ㸯 A^: Well^, where are you going to take me for my birthday?

B^: 33 .

A^: How about that Italian restaurant near the station?

B^: That sounds good^.

䐟 Probably^, I’ll have to work overtime on that day^. 䐠 What do you have in mind?

䐡 We can’t go out that night^. 䐢 Do you know who will come?

ၥ㸰 A^: Where did you go for your high school trip?

B^: I went to Tokyo^. And I visited ^“Tokyo Skytree^” with my friends^. A^: 34 .

B^: The view was amazing^. I’d love to go there again^.

䐟 When will you visit next time?

䐠 I’ve never seen the tower^. 䐡 What did you think about it?

䐢 How is it?

ၥ㸱 A^: What are you listening to^, Kerry?

B^: The new single by the King Kangaroo^. It’s not bad^, but I liked the last one better^.

A^: Maybe^, you’ll come to like it better if you 35 . B^: Actually^, I’ve heard it four times already^.

䐟 listened to it much harder^. 䐠 play it a few more times^.

䐡 stop playing it for a few minutes^. 䐢 were to see me playing it for you^.

(12)

ၥ㸲 A^: We shouldn’t have come to this beach today^. B^: I think so^, too^. It’s so crowded^.

A^: When did this beach become so popular?

B^: 36 .

䐟 Perhaps^, it hasn’t become so popular now^. 䐠 I know you don’t like swimming in the river^. 䐡 You’ll realize what to do on this beach^.

䐢 Well^, I heard that it appeared on TV last month^.

ၥ㸳 A^: How was the movie you saw last night?

B^: 37 . I should have seen the action movie instead^. A^:^“In the Jungle^”? I want to see it^, too^.

B^: How about going together next Sunday?

䐟 More interesting than expected^. 䐠 Very excited^.

䐡 Rather disappointing^. 䐢 More than twice^.

እ ᅜ ㄒ 䠄 ⱥ ㄒ 䠅