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2016年7月27日 星期三

台灣為什麼會缺電、限電 ?黃重球:別讓所有問題,都變成「相信或不相信」,台電關鍵數據大公開???

【台電黃重球:別讓所有問題,都變成「相信或不相信」】
今(27)日台北高溫飆至38.5度,台電最高用電達到3582.1萬瓩,呈現橙色燈的供電警戒,是歷史用電新高。上任台電董事長四年的黃重球黃重球究竟如何看待台灣的電力問題?他接受財訊專訪:
問:台灣未來究竟缺不缺電,該怎麼判斷?
⋯⋯更多


請問,台灣為什麼會缺電、限電?????
台灣為什麼會缺電、限電?????

台電公司昨天自己公布的數字是全台全天的最大的用電量為33600MW,然後昨天台電公司自己官網上,不包括停機當中沒有發電的核一廠一號機與核二廠二號機的其餘台電系統機組當中,顯示為歲修中、檢修中、故障中的發電機組的容量加起來就超過3719MW的規模,這是超過昨天最高用電量33600MW的11%的比率!!! 你說這是不是在開玩笑?



這是今天上午11點(06/02/2106)當台灣進入用電高峰的時刻,在台電公司官網上「台電系統個機組發電」狀態的資訊網頁的銀幕截圖。


以昨天06/01星期三為例,台電公司自己官網上的「台電系統各機組發電量」資訊就明白顯示了,不包括標示為「歲修」狀態,但是事實上已經停機多時並沒有在發電的兩部核電機組,目前台電手上處於故障停機、降載檢修、歲修中的機組容量加總起來高達3719.9MW的規模,你可知道就算台電現役的核一、核二廠的四部反應爐機組加總起來也不過就是3242MW的規模嗎。

在台電公司列為無法正常發電的這超過3719MW規模的發電機組當中(請注意,再強調一次,上述的數字是並不包括停機當中的台電核一一號機組與核二二號機組的兩座機組的數字),

其中列為歲修中的機組有1623.5MM

列為檢修中的機組有821.7MW (經詢問台電公司,目前有數部機組大幅降載進行檢修中。)

處於故障狀態的機組有1274.7MW (相形之下,台電核一廠兩部機組加總起來的發電量為1272MW)

其他還有一堆火力機組是處於「環保限制」、「運轉限制」的狀態,必須降載運轉。

當然,基於環保、減碳的原則,只要是達到「環保限制」、「運轉限制」的狀態必須降載運轉的機組就必須嚴格遵守規定降載甚至停機,這一點毫無疑義。


相較於往年的慣例,今年(2016)台電系統機組當中的核電與火力發電機組歲修的排程與往常五月底夏季用電尖峰期以前就全部歲修完畢可以上線的情況有所不同。

★★ PS. 圖片一說明:這是2011年的時候台電系統機組核電與火力發電機組的部分歲修的排程。相較於往年的慣例,今年(2016)台電系統機組當中的核電與火力發電機組歲修的排程與往常五月底夏季用電尖峰期以前就全部歲修完畢可以上線的情況有所不同。歷年台電機組維修排程歷史資料提供:吉正然
但是,台電公司昨天自己公布的數字是全台全天的最大的用電量為33600MW,然後昨天台電公司自己官網上,不包括停機當中並沒有發電的核一廠一號機與核二廠二號機的其餘台電系統機組當中,顯示為歲修中、檢修中、故障中的發電機組的容量加起來就超過3719MW的規模,這是超過昨天最高用電量33600MW的11%的比率!!! 你說這是不是在開玩笑?(真的離譜,所以要再說一次。)

此外,台電公司一直很低調的不情願讓社會大眾了解的是,手上已經投入台幣超過3361億元而且都動工興建好幾年,現在已經陸續開始進入驗收、並聯運轉階段的新發電廠的規模高達6677.8MW,目前第一部機組台電林口電廠800MW的新1號機組也已經並聯發電,預計今年10月份正式商轉,此外,根據台電公司官網的訊息顯示台灣還有民營電廠也陸續有6351MW的新發電容量會加入並聯發電的行列,扣除掉預已經開始陸續停機除役的10790MW機組,我們還是會有足夠的發電容量。


台電公司進行中的林口、通霄、大林電廠更新計畫執行情形。

當然,我們都還沒有提到未來數年間勢必會大幅增加的各種再生能源的發電機組的規模,政府原本已經訂定的計畫是在2020年的時候,將台灣的整體再生能源規模達到10858MW的規模,目前剛上任的小英政府已經明確表示會擴大提升再生能源的建設,因此未來台灣的再生能源發電規模會比原定的規模再大幅提升,毫無疑義。

而且,你知道嗎?以目前台灣已經完成的再生能源如此薄弱、微小的規模,今天的新聞報導已經正式指出,在昨天06/01中午的全台用電量最高峰的時候,台灣的以水力發電為主,搭配風力發電與太陽能發電的再生能源組合,加上抽蓄式水力發電的總發電量已經超過目前運轉中的四部核電廠反應爐的總發電量了。更何況,隨著新的再生能源發電設備源源不絕的加入運轉行列,台灣本土的再生能源的龐大潛力才剛剛要發揮而已。

請問看過這些真正的數據之後,如果電廠的經營管理、維護運轉正常的話,台灣哪裡會缺電????

台灣的發電廠不是不夠,而是經營管理,整體規劃上出現問題!!

更何況,台灣目前每年花費在對外購買能源的費用超過台幣兩兆兩千多億元,幾乎佔了台灣全年GDP的15%的規模,其中初始能源的比率當中,石油佔45.28%、煤炭佔34.06%、天然氣佔11.55%、核能佔8.66%(相形之下再生能源佔比目前僅有0.45%左右),而且,再生能源因為是運用在地的陽光、空氣、水為能源來發電的,因此是不會產生燃料成本的。

也就是說,我們台灣現在每年要砸台幣兩兆多的費用去向外採購能源,其中大約一半的比率超過一兆台幣的費用是用來當作是傳統火力發電與核能發電的燃料,每年花一兆多的燃料費,20年就得花超過20多兆台幣的費用(這還要保證化石燃料、核燃料在這期間不會漲價),否則光有發電廠沒有進口燃料可用的話,就算我們的電廠都是鑲金又包銀的也發不出一丁點電力可用,但是如果轉向使用再生能源發電,我們每年可以節省下龐大的對外能源採購費用,可以把這些資源拿來作為改善國內教育、醫療、環境、經濟、社福或是種種基礎建設的經費,並且因此而連帶明顯的改善在地的就業情況與真正在地的經濟產值。

至於今天北部、東北部地區和各地山區都會有局部大雨,用電量會大幅下降,原本供電就不會有問題,除非台電再接再厲的讓機組更大規模故障、降載檢修下去,那麼,如果真的發生這樣的狀況,那還是要歸因於,台灣發電廠不是不夠,但是卻是在於人為管理、運作上發生問題的狀況。

正本清源的解決之道,不是再去砸鉅資去蓋更多的高污染的燃煤火力發電廠,或是為了短期的應急需要,藉故去重新啟動原本就老舊、耗損不堪的危險核電反應爐,而是歸根究底的好好改善電廠的經營管理維修狀況,以及改革老舊過時,非要依賴高風險高污染的核電、燃煤不可的保守僵化經營心態。 ★★★ 以下的圖表是昨天(06/01/2016)中午用電尖峰時段的台電系統個機組的發電情況。真的必須要向台電公司中央電力調度中心的所有夥伴們致上最大敬意,在如此龐大數量的機組都有狀況的限制之下,最近的台灣電力調度狀況的確很棘手,謝謝電力調度中心所有辛勞的夥伴們,讓我們台灣安然度過用電尖峰時段,你們真的很厲害!!! 希望除了核電機組之外的那些歲修中,檢修中,故障中的機組可以很順利的加入供電行列,讓調度中心的夥伴們的日子比較好過一點。

2016年7月26日 星期二

FT:The human cloud: A new world of work;蘋論:機器人 就業終結者

蘋論搞錯了某些面向,新型的工作會被開創。
蘋論:機器人 就業終結者
2016年07月27日

在商場和家裡工作的機器人時代已經來臨,他們不但端茶送水、幫忙提東西,還會在你想找人講話時陪你聊天
現在和朋友聚餐加入的是外傭,很快你將看到一群聚餐親友的每個人背後站著一個可愛的機器人。貴婦們會競相比較誰的機器人是精品名牌,誰又換了新型號的名牌機器人。這是美麗新世界嗎?憂慮的是被機器人取代工作的勞工可能將永遠失業。

「新時代已來臨了」

鴻海與日本軟體銀行合作研發的服務型機器人Pepper前天正式在台亮相,獲得一銀、家樂福、國泰人壽、台新銀、亞太電信等企業首先使用。Pepper將以租賃方案切入台灣市場,含硬體、消費者互動服務、商業套件服務和售後服務等,月租費26888元台幣。這件事告訴我們一個新時代來臨了。
美國麻省理工學院(MIT)的《科技評論》自2001年開始,每年公布當年的「10大突破性技術」。此前公布的「2016年10大突破性技術」包括:免疫工程、精確編輯植物基因、語音介面、可回收火箭、知識分享型機器人、DNA應用商店、高效能太陽電池板、Slack通信軟體、特斯拉自動駕駛儀、Wi-Fi取電。其中知識分享型機器人的原型我們已經看到。
這種機器人可以學習任務,同時把知識傳到雲端,供其他機器人學習。其重要意義在於:如果不需要分別對所有類型的機器人單獨寫程式,就可以極大地加快機器人的發展進程。 

急需人工智慧人才


機器人的種類目前有二,工業機器人和服務機器人,前者早已用在工廠,形成自動化生產,像是汽車製造廠,已經排擠了許多工人的就業;後者是未來市場的寵兒,但也遠比工業型複雜,需要與人互動的能力,像是語音辨識、雲端運算、機器學習以及各種的感測技術等人工智慧。這個領域非常廣,還缺乏很多人才,年輕人要盡快學習這方面的技術,可以剛好趕上潮流,發揮所長。
日後還會出現機器人士兵,從事作戰任務、給需要異性或配偶的人機器人伴侶。令人擔憂的是以後櫃檯員、公寓管理員、保全、餐廳服務員、空姐、老師等工作都可能由機器人取代,這麼龐大人口的失業將是社會的災難。政府有義務辦理給予民眾新技術教育的機會,協助學有新技術人們就業。 




October 8, 2015 6:08 pm

The human cloud: A new world of work

©Jacey
Nestled in his “man cave”, a room crammed with cardboard boxes and fishing lures in his Rhode Island home, Set Sar is earning money by letting a company track the tiniest movements of his eyeballs through his computer’s webcam.
About 10,000 miles away, Adi Nagara is hiding from the heat in his air-conditioned bedroom in Jakarta, researching an Indonesian industry for a consultancy firm. Though they are doing different tasks for wildly different sums on different sides of the world, the two men are connected. They are both members of the “human cloud”.
Some of these tasks are as simple as looking up phone numbers on the web, typing data into a spreadsheet or watching a video while a webcam tracks your eye movements. Others are as complex as writing a piece of code or completing a short-term consultancy project.Employers are starting to see the human cloud as a new way to get work done. White-collar jobs are chopped into hundreds of discrete projects or tasks, then scattered into a virtual “cloud” of willing workers who could be anywhere in the world, so long as they have an internet connection.
The uniting factor is that these are not jobs but tasks or projects, performed remotely and on-demand by people who are not employees but independent workers. Much of it is, in effect, white-collar piecework. Employers spent between $2.8bn and $3.7bn globally last year on payments to workers and the online platforms that act as intermediaries in the human cloud, according to a recent Staffing Industry Analysts report.
To its champions — the people who run platforms and others who believe we are on the threshold of a flexible work revolution — the human cloud promises to eliminate skill shortages, ease unemployment black spots and create a global meritocracy where workers are rewarded solely for their output, regardless of their location, education, gender or race. Some even say it could return us to the age of the cottage industry, before we crammed into factories or offices and lost control over our work.
Chart: human cloud data
“What we see today is people taking ownership again of the means of production, because you just need a computer, your brain and a wifi connection to work,” says Denis Pennel, managing director of Ciett, the international lobbying organisation for private employment agencies. “So actually, Marx should be very happy!”
Critics turn to history for their analogies too, but they talk of dead-eyed operatives on production lines, not happy artisans. In the human cloud they see a wild west of unregulated virtual sweatshops, breaking down service sector work into its constituent parts, making people compete in a worldwide race to the bottom. “It makes Adam Smith’s famous division of labour in pin-making look modest,” says Guy Standing, an academic and author of several books about the “precariat” and the growth of insecure work.

Turkers and nerds

Whether the human cloud is more utopia or dystopia depends, at least in part, on where exactly in its hierarchy you find yourself.
Mr Sar is near the bottom, as he readily admits. “We’re just getting crumbs as far as what we’re getting paid for it,” says the 29-year-old from Providence, capital of America’s smallest state.
He joined the human cloud through Amazon’s Mechanical Turk, a site run by the online retailer where “requesters” pay “Turkers” to do simple microtasks that humans are still marginally better at than computers, such as transcribing audio clips, filling in surveys or tagging photos with relevant keywords. The name Mechanical Turk refers to a fake chess-playing machine from the 18th century that fooled onlookers into believing it was an automaton when in fact there was a person hiding inside. Amazon — whose tagline for the platform is “artificial artificial intelligence” — calls the jobs on offer “human intelligence tasks”, or HITs. Many of them only pay a few cents apiece.
Chart: human cloud data
On a good day, Mr Sar would earn about $5 to $7 an hour by doing batches of HITs in his free time (he also has a job in a warehouse). But after Amazon increased the fee it charged “requesters” to post HITs to 20 per cent of what they pay workers, he says HITs dried up and pay rates dropped. “Now we as workers have to be competing against other workers to grab these good HITs.” Lately he has discovered a newer site, Sticky Crowd, which shows him videos and web pages and uses his webcam to track exactly what he looks at and what he ignores — useful information for advertisers. The pay is better: a dollar for every 2-3 minutes of eye-tracking.
Not all the work on offer is so futuristic. Take the cloud call centres that assemble armies of “independent agents” who work from home, pay for their own phone and internet, and only get paid when they are actually on a call. The average “talk-time rate” at one large cloud call-centre is $0.25 per minute, though some clients also offer sales commission.
Further up the hierarchy are platforms like UpworkFreelancer and People per Hour, which feature more skilled tasks such as copywriting, IT and design work. Upwork, formed last year by a merger of two large platforms, is now the behemoth of the human cloud, processing about $1bn worth of payments from employers to workers last year (of which it takes a 10 per cent cut). The company took 10 years to reach $1bn, but reckons it will reach $10bn in another six. “It’s a thing that takes a long time at the beginning,” says Stephane Kasriel, its chief executive. “Then at some point it hits a tipping point, it becomes mainstream.”
Some of these sites invite workers to “bid” for the tasks on offer — specifying how quickly and for what fixed price they could do the work. Others offer payment by the hour. In most cases, employers and workers give each other star ratings after they finish a task, much like on eBay or Airbnb, allowing them to build a track record. Reputations are important: human cloud platforms know they need to link employers with good workers to encourage return visits, so many are starting to use “big data” algorithms to recommend certain workers for certain gigs.
People per Hour has set up a sister site, SuperTasker, which uses a smaller group of pre-screened workers to do fixed tasks in a fixed period of time for a fixed price: a 400-word blog post delivered in three hours costs $45, for example. Xenios Thrasyvoulou, the company’s founder, calls this “SKUs for work”. SKUs are stock keeping units — retailer shorthand for indistinguishable products.
Chart: human cloud data
Yet at the top of the human cloud’s hierarchy, “standardisation” is a dirty word. “It’s not a commodity — clients don’t choose on price,” says Daniel Callaghan, chief executive of UK-based MBA & Company. His platform, like US rival HourlyNerd, links companies with “consultants on demand”. Other specialist sites include Topcoder for computer programmers and Upcounsel for lawyers.
Consultants on MBA’s platform charge between £250 and £4,800 a day (then MBA adds its fee of 20 per cent). Mr Nagara, who is 30, is one of the platform’s consultants; he used to work for Australian investment bank Macquarie but moved back to Indonesia for family reasons. He reckons he earns more from his daily rate than he would as a full-time employee — though he sacrifices the security and benefits, a trade-off his parents do not understand. “They stayed with one company for decades, so when they see me being unemployed every two months they think ‘Jesus!’ They probably think I’m a disaster!”

Opportunities and costs

While many workers on these specialist sites are young and fleeing the corporate grind or topping up incomes, others are capitalising on a lifetime’s worth of knowledge. Nasa, the US space agency, once posted a challenge to find an algorithm that could predict solar flares: the winner (who Nasa paid $20,000) was a retired radio frequency engineer.

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It is not hard to see the promise of the human cloud for employers, who frequently complain about skills shortages and a lack of skilled migrant workers.
Mr Callaghan says the human cloud will make such problems disappear. “You can now get whoever you want, whenever you want, exactly how you want it,” he says. “And because they’re not employees you don’t have to deal with employment hassles and regulations.”
That is particularly useful for fast-growing start-ups. Dom Bracher, a 22-year-old founder of UK-based mobile marketing company Tapdaq, uses developers and designers in Scandinavia and central Europe. “There’s no need for someone to be in the same city as you,” he says.
Susan Lund, a partner at the McKinsey Global Institute, says the human cloud can improve social mobility, too, since it allows people to amass hard evidence of their abilities regardless of the formal qualifications on their CVs.
“For somebody who doesn’t have a degree from a top university or even a degree at all, accumulating those ratings is very important — to be able to say I’ve done X hours of coding and my average rating was Y — that’s very powerful,” she says.
Chart: human cloud data
The other consequence of work moving online is that more people should be able to do it: the housebound or people in locations where job opportunities are scarce.
The flipside is that workers in places where the cost of living is lower can undercut their peers in more expensive countries. “You can have someone in Gothenburg competing against someone in Dakar,” Prof Standing says.
Plenty of IT and call-centre work has been outsourced to countries like India but Prof Standing believes the next wave of “silent offshoring” will be more devastating for wages and conditions in the developed world.
It is hard to test this hypothesis, since most human cloud platforms are not listed and only disclose their data selectively. Still, a lot of work appears to gravitate to low-cost countries with skilled workforces: Upwork’s biggest markets after the US by worker earnings are India, the Philippines, Ukraine and Pakistan.
But Mr Sar and Mr Nagara are evidence that the picture is complex: low-paid work does not always drift east and high-paid work does not always drift west.

Contractors or staff?

Perhaps the thorniest problem of all for the human cloud is one that has also plagued Uber, the taxi app: when should an independent worker actually be classed as an employee?
Human cloud platforms usually classify workers as self-employed, which frees them from the requirement to pay minimum wages, employer taxes and benefits like sick pay.
But lawyers and workers are challenging them: last year a cloud platform called Crowdflower offered more than $500,000 to settle a US class action lawsuit from workers who said they were really “employees” and were therefore owed the minimum wage.
Most countries’ legal systems are struggling to keep up with these new forms of work. “In these arrangements, there’s really more than one employer — the law can’t grapple with this,” says Jeremias Prassl, a law professor at Oxford university.
Jonas Prising, chief executive of ManpowerGroup, an employment agency, predicts policymakers will impose more regulations on the new platforms soon.
“Who is taking care of these individuals? Who is providing the security in terms of taxation and social security? Who is doing the work is not known, who is paying the tax is not known, the age of the people doing the work is not known,” he says.
For all that, it can be a false comparison to contrast “insecure” human cloud work with “secure” traditional jobs — particularly at the bottom of the economic ladder.
Mr Sar has a job in a warehouse, but like many low-paid employees in developed countries, his rights and protections have been hollowed out. He is employed arm’s-length by an agency, which means he can be fired on the spot and is ineligible for many benefits. In the warehouse he wears an earpiece called “The Jennifer unit”, a robot in his ear that tells him what to do and tracks his performance and his downtime.
The human cloud might not pay much, it might be monotonous, but it gives him a sense of control. “Growing up through the years I’ve always worked for someone else. You’re treated as a number and not a human,” he says.
But his work in the cloud is different. “I can stop whenever I want. I can take a break, or eat something,” he says. “The idea of being my own boss is what really attracted me.”

2016年7月25日 星期一

Google Took Different Approaches Than Yahoo. Verizon to Pay $4.8 Billion for Yahoo’s Core Business


The Wall Street Journal

12 小時
In early 2000, Yahoo stood at the internet’s pinnacle, commanding the world’s most trafficked website and a $125 billion market value. Around that time, an upstart called Google was emerging as a destination for search.
A number of factors led to Google’s and Yahoo’s diverging fates but at the core of Google’s success has been a consistent management team that has focused relentlessly on technology serving its massive online-advertising…
ON.WSJ.COM|作者:JACK NICAS





Why Yahoo Sold Itself


美國電信巨擘 Verizon 將以超過 48 億美元買下 Yahoo! 的核心業務,預計將於美國時間星期一早上,股市開盤前正式宣佈。本交易幾乎已經底定,但細節有待正式發佈。
根據知情人士透露,這項交易包含了 Yahoo! 所持有的一些房地產資產,而一些智慧財產權將會被分離出售。而 Yahoo! 將繼續保有阿里巴巴以及日本 Yahoo! 的股份,這兩部分的總價值達 400 億美元。

Verizon to Pay $4.8 Billion for Yahoo’s Core Business

Founded in 1994, Yahoo was one of the last independently operated pioneers of the web and was once valued at $125 billion.

【見證歷史】歷時23年,不當黨產條例終於通過!《政黨及其附隨組織不當取得財產處理條例》相關關鍵問題


【見證歷史】歷時23年,不當黨產條例終於通過!
1992年:時任立委的謝長廷,提出「人民團體法」終結特權經營的黨營事業。
2001年:監委黃煌雄完成黨產調查報告,行政院依據監察院調查報告向國民黨要求歸還,但國民黨只歸還一小部分。
2002年:行政院正式提出「政黨不當取得財產處理條例」,但國民黨不顧國家債信、不惜讓國庫跳票也要捍衛其不當取得的黨產。
到2016年前,黨產條例在立法院總共被國民黨杯葛高達306次,連交付委員會討論的機會都沒有。
而23年後的2016年7月25日,民進黨終於在取得國會過半的優勢下,完成《政黨及其附隨組織不當取得財產處理條例》立法,立法院長蘇嘉全於晚間8點26分敲下議事槌,宣布三讀通過,完成歷史性的立法。


---
立法院針對《政黨及其附隨組織不當取得財產處理條例》,截至今天晚間7時31分,此法案已進行到第31條,同時繼續挑燈夜戰,預料若無意外將三讀通過。民進黨團對於即將通過的黨團版,其中幾個關鍵問題,包括「附隨組織」、「受託管理人」、「推定為不當的財產範圍」、「追討黨產」、「防止脫產」等,均提出說明,「讓您秒懂」這個歷史性法案。
以下為《政黨及其附隨組織不當取得財產處理條例》相關關鍵問題:
1.追討對象:政黨、附隨組織、受託管理人。(§4)
1.1為何只針對1987年前成立的政黨?是不是針對國民黨立法?
因為只有在黨國不分的威權體制下,政黨才有能力不當取得國家或人民的財產。在黨產條例定義下,威權時期成立的政黨都在清查範圍內,總共有10個,其中包括中國國民黨,也包括民主進步黨。
目前在內政部登記有案的政黨高達302個,但在動員戡亂時期結束以後,國家法治已經正常化,政黨比較沒有辦法再用黨國不分的手法取得財產,所以特別立法時,沒有必要將民主時代的無辜政黨納入清查跟處理的範圍,也可節省政府調查的人力物力。
1.2什麼是附隨組織?為什麼除了國民黨之外還要處理其他組織?
國民黨除了本身擁有龐大的黨產,還成立了許多的「附隨組織」,例如民眾服務社、救國團、婦聯會、中影、中廣、中投等黨營事業。這些附隨組織,也都因為威權時期國庫通黨庫的關係而累積了龐大的財產。因為不符合民主時代的標準,也就是實質法治國原則,都在本法清理的範圍內。
這些附隨組織當初財產的來源不當,但有些現在已經脫離了國民黨的控制,如果當初是用合理的價格轉賣,追討的對象就是國民黨,跟國民黨要回轉賣獲得的那筆錢。
如果是用不合理的價格半買半送,有脫產或A黨產嫌疑的,或是透過改組的方式而脫離國民黨控制的,因為財產來源不當,都還是在本法追討的範圍內,要證明沒有不當,否則都要歸還給國家。
1.3什麼是受託管理人?
政黨或附隨組織可能把財產信託給別人,或是借用人頭登記財產,這些也都在追查範圍之內。
2.追討範圍:推定為不當的財產範圍(民進黨團第5條草案)
2.1現有財產:
條例公布日起所有現存財產,除了黨費、政治獻金、競選補助金以外,全部推定為不當取得財產。
2.2已移轉的財產:
1945年8月15日起以無償或顯不相當對價取得的財產,除了黨費、政治獻金、競選補助金以外,在條例公布日前已經移轉給他人的財產,也全部推定為不當取得財產。
3.追討方式:推定不當黨產→無反證則歸還國家、地方或原權利人所有→已移轉給他人的則追討轉賣所獲得的那筆錢 (第5、第6)
被推定為不當取得的財產,必須向委員會舉出事證,證明不是不當取得,否則都要歸還給國家、地方政府或是原權利人。即使已經賣給別人,也要追討當初轉賣所獲得的那筆錢。
例如帝寶,當年是國民黨黨營事業中廣接收日產而來,後來用90億賣給建設公司蓋豪宅,必須將90億歸還。
4.防止脫產(第9、27)
條例公布日所有被推定為不當的現有財產,全部都禁止處分,並且凍結帳戶、限制登記,就算處分也不生效力。
除非能提出證據,證明財產不是不當取得,並且經過委員會認定同意,否則就必須進入後續的歸還程序,移轉回國家、地方或原權利人所有。
如果違反了禁止處分的規定,還會處罰交易金額一倍到三倍的罰鍰。
例如:國民黨黨營事業在台北車站C1雙子星的土地,可以要求地政機關限制移轉登記。在立法公布日後、限制移轉登記前,國民黨假如以50億元賣出,賣出契約無效,並且要處罰50億到150億的罰鍰。
5.需申報現有財產及過去財產移轉情形(第8條、第26)
被追討的對象需自行申報現有的財產有哪些,這些財產取得的日期及來源。同時,也需申報自1945年8月15日起,已賣出或移轉的財產有哪些,這些財產分別賣給或移轉給誰?賣了多少錢。
被追討的對象必須自行舉出事證,證明取得沒有不當,經過委員會認定同意,才能解除禁止處分、不用歸還,否則都要歸還。即使是過去已經賣出的財產,也要歸還賣掉的價款。
若逾期申報將處罰50萬到250萬元,每逾期10天處罰一次,處罰超過5次還不申報,就認定那筆財產是不當取得必須歸還。
6.惡意脫產、低價賣出、侵佔黨產也在追討範圍之內(第6條)
委員會調查過程中,如果發現有人沒有正當的理由,就免費或用不合理的低價獲得不當黨產,這些人可能是人頭、也可能侵佔了國民黨黨產,因為來源都是不當取自國家或人民,所以也都必須要歸還。
7.不繳罰鍰就直接扣政黨補助金(第32條)
依此條例規定所處罰的罰鍰,如果經過限期繳納還不繳納,主管機關可以直接從國家發給政黨的競選費用補助金直接扣除抵充。

2016年7月24日 星期日

2016桃園鍾肇政文學獎 號稱總獎金200萬元;第39屆時報文學獎???



2016桃園鍾肇政文學獎


literature.typl.gov.tw/

號稱總獎金200萬元



第39屆時報文學獎???

輕痰萬事屋新增了 4 張相片
【後文學獎時代】
  今天的大新聞,「時報文學獎」停辦了。
  今年《中國時報》動作頻頻,開卷收掉,人間縮編,主編換人,此事早有預兆。只是沒想到,堂堂三十八屆的文學獎竟以版面邊緣的「小啟」結束這一回合。下午,和一文青朋友吃飯,他哀叫著已經投稿,印費和郵費收不回來,「但有什麼辦法呢?」
  時報文學獎,1978年開辦,2016年「暫時 」告終。我翻出老師贈與的、非賣品的《時報文學獎史料索引(1978-1989)》,第一屆,那些獲獎者的名字與臉孔,還那麼年輕。


果子離


十八年前,與友人談到,真希望大報文學獎消失掉。
友人削了我一頓,說:「你不要在那邊講空話,若不是文學獎,像我這種沒背景、沒資歷的人,作品怎樣被看見?」
友人參加過皇冠小說獎,以及地方文學獎,長短篇小說得以分別出版,但還積壓著幾部台灣歷史長篇,不獲青睞。後來我向某編輯推薦,她又出版了幾本書。但最重量級的歷史長篇,還在等待徵文機會參加。


多年來,談到文學獎話題,我就想起她那句話。
在以前那個時代,文學作品出書,幾乎唯賴副刊培養知名度,而文章見報,若非與主編關係良好,便是在文學獎脫穎而出,否則曝光率微乎其微。文學獎因為採匿名制,大小牌無牌的寫作者一律平等。不知造就多少原本名不見經傳的作家。
微文學獎,多少人被髮左衽矣。
現在時代不一樣了,得獎效應稀釋了不少,但得獎後還是擁有很多資源。
然而要不要辦文學獎是主辦者的自由,外人不好說什麼。只不過,徵文公布了,卻在截稿前一小段時間突然喊卡,頭洗一半不洗了,這不是文學獎該不該辦的問題,這是怎麼這麼混帳的問題。

日本遊覽車司機的行車紀錄器

十幾年前,我在當日本當地導遊的時候,曾經對於遊覽車巴士的司機在下班時,從駕駛座附近退出一張紙製圓盤一事感到好奇。詢問下才發覺,該紙製圓盤記錄了那天開了幾小時,每個時段的時速為何的資料。司機說,如果有違規的話,相關人士都會被連坐處分。
嗯,臺灣有這個機制嗎?沒有的話,說什麼都沒有用的。

2016年7月23日 星期六

Uniqlo如何贏過香港服裝



【Uniqlo如何把香港服裝殺過片甲不留?】
/Uniqlo比香港隊聰明的一點在於,雖然我也醜,但我Cheap,並且變法地玩技術。Uniqlo的核心優勢之一,就是新面料的研發,Fleece、輕羽絨、Heattech,這些有技術含量的材料賦予了基本款更高的附加價值。反觀香港品牌,在創作上沒有方向、沒有自我,顧客是感覺到的。/
香港品牌,在創作上沒有方向、沒有自我,顧客是感覺到的。
HK.THENEWSLENS.COM|由信報財經月刊, TNL 上傳

2016年7月22日 星期五

腦殘公誤人員:防酒駕政院出招 考慮補助餐廳設酒測器

蕭志強分享了李嘉貼文
腦殘公誤人員只想多花錢。所有餐廳都要,得花幾十億吧?就學美日提高刑罰不就得了?
李嘉
可以不花錢的辦法不想,盡想些要花錢的,酒測器誰會去用?
自由心證罷了...壞了誰修?
是要嚴法,不是補助,腦殘嗎
交通部21日上午赴行政院會報告「精進道路交通安全作為」,針對防止酒駕…
NEWTALK.TW

2016年7月21日 星期四

一樣台灣人民 兩個退休世界(詹明勇)

這篇沒有談:多少人可能沒退休金。



焦點評論:一樣台灣人民 兩個退休世界(詹明勇)
2016年07月22日
公僕月退俸享富饒

.......我的朋友55歲,從公部門退休,年薪超過百萬,身體健朗,還養了農地待價而沽。
我的另一位朋友也從職場退下來了。大學畢業後他就待在這家機械工廠,大陸正夯熱的時候也曾經幫他的老闆到中國設廠。只是好景不常,中國市場競爭厲害,又回到台灣以穩定的步調接單生活。30年過去了,去年初在海外展銷提重物閃了腰部,就一直不舒服。回國後,老闆交辦的事情漸漸應付不來。我的朋友知道私人公司的特質,想想年資也到了,就提出辭呈。老闆當然有所慰留,但急流勇退才是智慧。朋友堅持走人,不想耽擱公司的業務,也可以活絡年輕同仁的升遷。人事部門結算後告訴他可以領月退大約3萬出頭,換成一次領回退休金大概比較不划算。過去的風光,煙消雲散,沒有還清的房貸大概勉強可以解決,夠了!這位在傳統產業工作的老朋友一身疲憊的和我吃飯,分享經驗。直說:「錢沒關係,趁身體還健康的時候,早點退休。」
我的朋友60歲,從傳統產業退休,月領3萬餘,扣除房貸利息,尚可勉強存活。
一樣台灣人民,兩個退休世界。公部門退休的資深公民,也許真的一輩子的忍辱負重,但退休後的生活無虞,甚且比多數受薪階級的民眾都還有餘裕。9成以上的國民,從非公部門退休,他們領的月退俸都很勉強的支撐生活的基本開銷,有些人的月退俸甚至低於最低工資的水準。沒有人想製造對立,但公部門的退休制度卻把台灣分成兩個世界。9成受薪族群支撐了公部門員工的尊嚴,可惜這些受供養的公務員卻忘記了他們的優雅是來自於很多人的容忍。
奮鬥一輩子,工作半甲子,卻有不同的老年。我們國民平均壽命80歲,這些退休的資深公民,未來20年因為生活的方式不同,不容易有對話的機會,我們的社會能夠祥和嗎?領太多,可以少爭取一點;領太少,可以多補助一些。台灣就會更好! 
大學教師 
更厲害的是,這制度誰創造出來的?公務員
他們知道他們該交42.65%的薪水出來才能退休領這麼多嗎? 知道,銓敘部一直都知道,報告上星期也發布了
他們打算交12%退撫基金,本來只該領目前28%的退休金 (12%/42.65%=28%)
不過只要國庫永遠貼補不就結了?反正國家錢愛怎麼花由公務員決定,不由勞工決定.....

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