IVOD_ID |
149766 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/149766 |
日期 |
2024-03-13 |
會議資料.會議代碼 |
委員會-11-1-26-5 |
會議資料.會議代碼:str |
第11屆第1會期社會福利及衛生環境委員會第5次全體委員會議 |
會議資料.屆 |
11 |
會議資料.會期 |
1 |
會議資料.會次 |
5 |
會議資料.種類 |
委員會 |
會議資料.委員會代碼[0] |
26 |
會議資料.委員會代碼:str[0] |
社會福利及衛生環境委員會 |
會議資料.標題 |
第11屆第1會期社會福利及衛生環境委員會第5次全體委員會議 |
影片種類 |
Clip |
開始時間 |
2024-03-13T10:28:16+08:00 |
結束時間 |
2024-03-13T10:39:25+08:00 |
影片長度 |
00:11:09 |
支援功能[0] |
ai-transcript |
支援功能[1] |
gazette |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/7ed54bd69a3b6903c76f884008139d5c14b75c67118f492bf8ba9b0039caa7a6130a6e79d11c52415ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
楊曜 |
委員發言時間 |
10:28:16 - 10:39:25 |
會議時間 |
2024-03-13T09:00:00+08:00 |
會議名稱 |
立法院第11屆第1會期社會福利及衛生環境委員會第5次全體委員會議(事由:邀請勞動部部長列席報告業務概況,並備質詢。
【3月13日及14日二天一次會】) |
gazette.lineno |
621 |
gazette.blocks[0][0] |
楊委員曜:(10時28分)謝謝主席。主席,請一下許部長。 |
gazette.blocks[1][0] |
主席:請許部長。 |
gazette.blocks[2][0] |
許部長銘春:楊委員好。 |
gazette.blocks[3][0] |
楊委員曜:部長好。部長,今天的業務報告是有關年金改革準備的部分,部裡面這邊還是一直停留在蒐集意見,對不對? |
gazette.blocks[4][0] |
許部長銘春:蒐集意見跟溝通。 |
gazette.blocks[5][0] |
楊委員曜:會不會蒐集意見跟溝通的時間太長了?我知道這是一項很嚴峻的工程,我也不是想為難你,可是我覺得好像每一次的業務報告中有關年改的部分,大概都是一直停留在蒐集意見跟評估,這樣一來,到底年改什麼時候可以啟動、什麼時候可以落實,讓廣大的勞工可以得到安心,到底是什麼時候? |
gazette.blocks[6][0] |
許部長銘春:委員,關於期程部分,我們會來通盤的規劃,只是說因為…… |
gazette.blocks[7][0] |
楊委員曜:部長,我打岔一下,假如說今天來業務報告就已經有期程,那我可能還可以接受。可是這6年來,部長也已經任滿6年了,是一個非常長壽的部長,但對於跟勞工這麼息息相關、影響這麼重大的一個政策,卻一直停留在準備、蒐集意見以達到共識的階段,這點本席真的沒有辦法接受! |
gazette.blocks[8][0] |
許部長銘春:謝謝委員。因為這部分的確不容易,因為…… |
gazette.blocks[9][0] |
楊委員曜:我知道。 |
gazette.blocks[10][0] |
許部長銘春:因為勞工人口數實在太多,然後每個產業的職業勞工意見又都不同,關心的點也都不同,所以我也認為其實應該要更…… |
gazette.blocks[11][0] |
楊委員曜:我曾經在委員會跟部長討論過,我覺得任何一項改革都不可能有共識。我也知道勞工的年金改革為什麼困難,因為他原本可以領到的給付就少,廣大的受薪階級勞工,並沒有因為臺灣經濟成長而使其薪資等比例增加。所以要增加保費有一定的阻力,要延後退可能會引發很大的風波。我知道困難在哪裡,可是也正因為困難,所以選民才給民進黨機會,就是要民進黨面對困難。 |
gazette.blocks[11][1] |
記得我們在從事軍公教年改時,大概整個民進黨黨團受影響最大的就是我,因為澎湖的軍公教比例太高了!但我還是戴著鋼盔挺過了年改,我又當選兩屆了。如同蔡英文總統講的,應該要改革的就是必須要改革,必須要想出一套方案讓退休的不恐懼,讓正在繳保費的心安,這是我們的責任。這幾年提撥成為改革唯一的選項,這個本席也不反對,甚至我已經提案把政府負擔最終給付責任入法。為什麼我這麼重視這件事情?因為必須讓勞動者有一個安定的心情,讓他知道不管任何人執政,都不會放棄這一千多萬的勞工朋友,這一千多萬對於臺灣經濟有卓著貢獻的勞工,所以我覺得我們必須要去面對,現在就是這樣。就像我剛才講的,我知道改革困難,為什麼?不要說減少給付,就以目前的給付來看,目前請領勞工給付的人數大概有174萬…… |
gazette.blocks[12][0] |
許部長銘春:對。 |
gazette.blocks[13][0] |
楊委員曜:平均每個月領到的是一萬八千多,可是臺灣最低生活費,以臺北市來講,已經高達一萬九千多。臺北市以外的地方平均值也將近一萬五千,現在領這樣子,在臺北市已經未達最低生活費標準了,萬一再減少給付的話怎麼辦? |
gazette.blocks[14][0] |
許部長銘春:對。跟委員報告,以臺灣的產業勞工來看,退休給付包括兩個:一個勞保,另外一個就是勞退…… |
gazette.blocks[15][0] |
楊委員曜:勞退。 |
gazette.blocks[16][0] |
許部長銘春:這兩個加起來……當然還有健保、長照,這都是照顧我們的退休人員…… |
gazette.blocks[17][0] |
楊委員曜:健保跟長照是另外一回事,我們聚焦在勞工部分,也就是勞保與勞退。我認為勞退比例太低了,自提的部分太低了…… |
gazette.blocks[18][0] |
許部長銘春:自提比較低,但雇提也達到七百多萬…… |
gazette.blocks[19][0] |
楊委員曜:大概是這樣子,全體提繳數在106年時,大概是百分之十四點多…… |
gazette.blocks[20][0] |
許部長銘春:對、對。 |
gazette.blocks[21][0] |
楊委員曜:現在呢? |
gazette.blocks[22][0] |
許部長銘春:自提部分,去年是14.17%…… |
gazette.blocks[23][0] |
楊委員曜:14.17%? |
gazette.blocks[24][0] |
許部長銘春:對,人數是106萬。 |
gazette.blocks[25][0] |
楊委員曜:好,14.17%。就像部長講的,沒有錯,我們對勞工退休保障的設計架構是在勞保與勞退,問題是勞退本身有一個現象,即這百分之十四點多,你仔細去看,薪資所得越高的,越願意配合自提;越低的,因為他所得本來就低,所以要再提出6%可能有困難度。 |
gazette.blocks[26][0] |
許部長銘春:還有雇提6%,這6%是雇主一定要提撥的。 |
gazette.blocks[27][0] |
楊委員曜:對,我知道。那6%大家都有…… |
gazette.blocks[28][0] |
許部長銘春:對。 |
gazette.blocks[29][0] |
楊委員曜:我現在講的是6%加6%…… |
gazette.blocks[30][0] |
許部長銘春:自提等於另外…… |
gazette.blocks[31][0] |
楊委員曜:特別是薪資低的勞工來看,6%加6%才足以保障他的退休生活!因為他本來就低薪,可以領的勞保給付本來就低,然後又因為職涯過程、生活所需、教養子女、孝敬父母,所以自提6%對他來講,會馬上面臨生活的困頓,部長懂我的意思嗎? |
gazette.blocks[32][0] |
許部長銘春:我知道。如果是低薪可能…… |
gazette.blocks[33][0] |
楊委員曜:多數都是低薪,既是低薪,自提的很少。 |
gazette.blocks[34][0] |
許部長銘春:我們現在有統計,月投保薪資平均大概是三萬七千;如果以三萬七千來看,他的勞保,按照現制,大概領一萬七千左右。如果再加上勞退,就是雇提,只算雇提不算自提,大概一萬,所以勞保加勞退,大概二萬七千七百。以現在一個退休勞工的平均月投保薪資三萬七千來看,我們平均大概抓三萬七千,這樣領起來有二萬七千多,替代率68%。 |
gazette.blocks[35][0] |
楊委員曜:這種平均值會比較看不到真正的弱勢,保障弱勢是民進黨邁向執政最重要的一個東西。目前勞保加勞退的平均值有二萬七千,看起來好像夠,暫且不管目前的通貨膨脹,可是我們是不是能夠多替這些低薪的勞工想想辦法? |
gazette.blocks[36][0] |
許部長銘春:弱勢要特別照顧,我覺得委員您的建議,我們會…… |
gazette.blocks[37][0] |
楊委員曜:我也知道很困難,可是我常說,不困難的事怎麼輪得到我們做?我最後問一個問題,本席已經提出由政府擔負最終的支付責任保證,對這樣的提案,勞動部的立場會支持嗎? |
gazette.blocks[38][0] |
許部長銘春:我們支持。 |
gazette.blocks[39][0] |
楊委員曜:好,謝謝部長,謝謝主席。 |
gazette.blocks[40][0] |
主席:謝謝楊曜委員。我們現在休息10分鐘。 |
gazette.blocks[40][1] |
休息(10時39分) |
gazette.blocks[40][2] |
繼續開會(10時50分) |
gazette.blocks[41][0] |
主席:接下來請王育敏委員。 |
gazette.agenda.page_end |
286 |
gazette.agenda.meet_id |
委員會-11-1-26-5 |
gazette.agenda.speakers[0] |
黃秀芳 |
gazette.agenda.speakers[1] |
陳昭姿 |
gazette.agenda.speakers[2] |
陳菁徽 |
gazette.agenda.speakers[3] |
盧縣一 |
gazette.agenda.speakers[4] |
邱鎮軍 |
gazette.agenda.speakers[5] |
蘇清泉 |
gazette.agenda.speakers[6] |
涂權吉 |
gazette.agenda.speakers[7] |
王正旭 |
gazette.agenda.speakers[8] |
楊曜 |
gazette.agenda.speakers[9] |
王育敏 |
gazette.agenda.speakers[10] |
李坤城 |
gazette.agenda.speakers[11] |
林淑芬 |
gazette.agenda.speakers[12] |
楊瓊瓔 |
gazette.agenda.speakers[13] |
林月琴 |
gazette.agenda.speakers[14] |
伍麗華Saidhai‧Tahovecahe |
gazette.agenda.speakers[15] |
李彥秀 |
gazette.agenda.speakers[16] |
羅智強 |
gazette.agenda.speakers[17] |
牛煦庭 |
gazette.agenda.speakers[18] |
劉建國 |
gazette.agenda.speakers[19] |
王鴻薇 |
gazette.agenda.speakers[20] |
張雅琳 |
gazette.agenda.speakers[21] |
黃仁 |
gazette.agenda.speakers[22] |
吳春城 |
gazette.agenda.speakers[23] |
陳瑩 |
gazette.agenda.speakers[24] |
廖偉翔 |
gazette.agenda.speakers[25] |
林德福 |
gazette.agenda.speakers[26] |
葉元之 |
gazette.agenda.page_start |
193 |
gazette.agenda.meetingDate[0] |
2024-03-13 |
gazette.agenda.gazette_id |
1131301 |
gazette.agenda.agenda_lcidc_ids[0] |
1131301_00005 |
gazette.agenda.meet_name |
立法院第11屆第1會期社會福利及衛生環境委員會第5次全體委員會議紀錄 |
gazette.agenda.content |
邀請勞動部部長列席報告業務概況,並備質詢 |
gazette.agenda.agenda_id |
1131301_00004 |
transcript.pyannote[0].speaker |
SPEAKER_00 |
transcript.pyannote[0].start |
6.13971875 |
transcript.pyannote[0].end |
8.02971875 |
transcript.pyannote[1].speaker |
SPEAKER_02 |
transcript.pyannote[1].start |
8.41784375 |
transcript.pyannote[1].end |
9.21096875 |
transcript.pyannote[2].speaker |
SPEAKER_02 |
transcript.pyannote[2].start |
13.56471875 |
transcript.pyannote[2].end |
14.13846875 |
transcript.pyannote[3].speaker |
SPEAKER_00 |
transcript.pyannote[3].start |
14.13846875 |
transcript.pyannote[3].end |
14.17221875 |
transcript.pyannote[4].speaker |
SPEAKER_00 |
transcript.pyannote[4].start |
14.54346875 |
transcript.pyannote[4].end |
15.25221875 |
transcript.pyannote[5].speaker |
SPEAKER_00 |
transcript.pyannote[5].start |
15.58971875 |
transcript.pyannote[5].end |
16.95659375 |
transcript.pyannote[6].speaker |
SPEAKER_00 |
transcript.pyannote[6].start |
23.16659375 |
transcript.pyannote[6].end |
26.20409375 |
transcript.pyannote[7].speaker |
SPEAKER_00 |
transcript.pyannote[7].start |
26.50784375 |
transcript.pyannote[7].end |
30.06846875 |
transcript.pyannote[8].speaker |
SPEAKER_00 |
transcript.pyannote[8].start |
30.81096875 |
transcript.pyannote[8].end |
34.32096875 |
transcript.pyannote[9].speaker |
SPEAKER_00 |
transcript.pyannote[9].start |
35.53596875 |
transcript.pyannote[9].end |
37.66221875 |
transcript.pyannote[10].speaker |
SPEAKER_02 |
transcript.pyannote[10].start |
37.66221875 |
transcript.pyannote[10].end |
39.02909375 |
transcript.pyannote[11].speaker |
SPEAKER_00 |
transcript.pyannote[11].start |
42.01596875 |
transcript.pyannote[11].end |
42.77534375 |
transcript.pyannote[12].speaker |
SPEAKER_00 |
transcript.pyannote[12].start |
43.19721875 |
transcript.pyannote[12].end |
44.17596875 |
transcript.pyannote[13].speaker |
SPEAKER_00 |
transcript.pyannote[13].start |
44.81721875 |
transcript.pyannote[13].end |
48.17534375 |
transcript.pyannote[14].speaker |
SPEAKER_00 |
transcript.pyannote[14].start |
48.96846875 |
transcript.pyannote[14].end |
54.16596875 |
transcript.pyannote[15].speaker |
SPEAKER_00 |
transcript.pyannote[15].start |
54.77346875 |
transcript.pyannote[15].end |
56.54534375 |
transcript.pyannote[16].speaker |
SPEAKER_00 |
transcript.pyannote[16].start |
57.18659375 |
transcript.pyannote[16].end |
62.60346875 |
transcript.pyannote[17].speaker |
SPEAKER_00 |
transcript.pyannote[17].start |
63.56534375 |
transcript.pyannote[17].end |
66.70409375 |
transcript.pyannote[18].speaker |
SPEAKER_00 |
transcript.pyannote[18].start |
67.17659375 |
transcript.pyannote[18].end |
71.90159375 |
transcript.pyannote[19].speaker |
SPEAKER_00 |
transcript.pyannote[19].start |
72.69471875 |
transcript.pyannote[19].end |
73.99409375 |
transcript.pyannote[20].speaker |
SPEAKER_00 |
transcript.pyannote[20].start |
74.24721875 |
transcript.pyannote[20].end |
82.12784375 |
transcript.pyannote[21].speaker |
SPEAKER_00 |
transcript.pyannote[21].start |
83.51159375 |
transcript.pyannote[21].end |
86.81909375 |
transcript.pyannote[22].speaker |
SPEAKER_00 |
transcript.pyannote[22].start |
86.97096875 |
transcript.pyannote[22].end |
86.98784375 |
transcript.pyannote[23].speaker |
SPEAKER_00 |
transcript.pyannote[23].start |
87.76409375 |
transcript.pyannote[23].end |
88.64159375 |
transcript.pyannote[24].speaker |
SPEAKER_02 |
transcript.pyannote[24].start |
89.36721875 |
transcript.pyannote[24].end |
93.61971875 |
transcript.pyannote[25].speaker |
SPEAKER_00 |
transcript.pyannote[25].start |
93.61971875 |
transcript.pyannote[25].end |
101.60159375 |
transcript.pyannote[26].speaker |
SPEAKER_01 |
transcript.pyannote[26].start |
95.96534375 |
transcript.pyannote[26].end |
95.98221875 |
transcript.pyannote[27].speaker |
SPEAKER_02 |
transcript.pyannote[27].start |
95.98221875 |
transcript.pyannote[27].end |
97.39971875 |
transcript.pyannote[28].speaker |
SPEAKER_01 |
transcript.pyannote[28].start |
97.39971875 |
transcript.pyannote[28].end |
97.43346875 |
transcript.pyannote[29].speaker |
SPEAKER_02 |
transcript.pyannote[29].start |
97.43346875 |
transcript.pyannote[29].end |
97.45034375 |
transcript.pyannote[30].speaker |
SPEAKER_00 |
transcript.pyannote[30].start |
101.87159375 |
transcript.pyannote[30].end |
103.32284375 |
transcript.pyannote[31].speaker |
SPEAKER_00 |
transcript.pyannote[31].start |
104.08221875 |
transcript.pyannote[31].end |
106.39409375 |
transcript.pyannote[32].speaker |
SPEAKER_01 |
transcript.pyannote[32].start |
106.39409375 |
transcript.pyannote[32].end |
106.68096875 |
transcript.pyannote[33].speaker |
SPEAKER_00 |
transcript.pyannote[33].start |
106.95096875 |
transcript.pyannote[33].end |
109.38096875 |
transcript.pyannote[34].speaker |
SPEAKER_00 |
transcript.pyannote[34].start |
109.87034375 |
transcript.pyannote[34].end |
120.60284375 |
transcript.pyannote[35].speaker |
SPEAKER_00 |
transcript.pyannote[35].start |
121.00784375 |
transcript.pyannote[35].end |
136.51596875 |
transcript.pyannote[36].speaker |
SPEAKER_02 |
transcript.pyannote[36].start |
136.61721875 |
transcript.pyannote[36].end |
136.93784375 |
transcript.pyannote[37].speaker |
SPEAKER_02 |
transcript.pyannote[37].start |
137.51159375 |
transcript.pyannote[37].end |
139.84034375 |
transcript.pyannote[38].speaker |
SPEAKER_02 |
transcript.pyannote[38].start |
140.27909375 |
transcript.pyannote[38].end |
140.92034375 |
transcript.pyannote[39].speaker |
SPEAKER_02 |
transcript.pyannote[39].start |
141.32534375 |
transcript.pyannote[39].end |
142.75971875 |
transcript.pyannote[40].speaker |
SPEAKER_02 |
transcript.pyannote[40].start |
142.89471875 |
transcript.pyannote[40].end |
147.28221875 |
transcript.pyannote[41].speaker |
SPEAKER_00 |
transcript.pyannote[41].start |
142.96221875 |
transcript.pyannote[41].end |
144.02534375 |
transcript.pyannote[42].speaker |
SPEAKER_00 |
transcript.pyannote[42].start |
146.77596875 |
transcript.pyannote[42].end |
147.23159375 |
transcript.pyannote[43].speaker |
SPEAKER_02 |
transcript.pyannote[43].start |
147.73784375 |
transcript.pyannote[43].end |
153.96471875 |
transcript.pyannote[44].speaker |
SPEAKER_01 |
transcript.pyannote[44].start |
153.49221875 |
transcript.pyannote[44].end |
154.03221875 |
transcript.pyannote[45].speaker |
SPEAKER_00 |
transcript.pyannote[45].start |
154.03221875 |
transcript.pyannote[45].end |
154.84221875 |
transcript.pyannote[46].speaker |
SPEAKER_02 |
transcript.pyannote[46].start |
154.36971875 |
transcript.pyannote[46].end |
158.89221875 |
transcript.pyannote[47].speaker |
SPEAKER_00 |
transcript.pyannote[47].start |
158.52096875 |
transcript.pyannote[47].end |
165.62534375 |
transcript.pyannote[48].speaker |
SPEAKER_02 |
transcript.pyannote[48].start |
160.22534375 |
transcript.pyannote[48].end |
160.51221875 |
transcript.pyannote[49].speaker |
SPEAKER_00 |
transcript.pyannote[49].start |
166.50284375 |
transcript.pyannote[49].end |
170.67096875 |
transcript.pyannote[50].speaker |
SPEAKER_00 |
transcript.pyannote[50].start |
172.42596875 |
transcript.pyannote[50].end |
175.48034375 |
transcript.pyannote[51].speaker |
SPEAKER_00 |
transcript.pyannote[51].start |
175.75034375 |
transcript.pyannote[51].end |
179.83409375 |
transcript.pyannote[52].speaker |
SPEAKER_00 |
transcript.pyannote[52].start |
180.66096875 |
transcript.pyannote[52].end |
187.47846875 |
transcript.pyannote[53].speaker |
SPEAKER_00 |
transcript.pyannote[53].start |
188.52471875 |
transcript.pyannote[53].end |
189.14909375 |
transcript.pyannote[54].speaker |
SPEAKER_00 |
transcript.pyannote[54].start |
190.54971875 |
transcript.pyannote[54].end |
195.40971875 |
transcript.pyannote[55].speaker |
SPEAKER_00 |
transcript.pyannote[55].start |
196.13534375 |
transcript.pyannote[55].end |
197.18159375 |
transcript.pyannote[56].speaker |
SPEAKER_01 |
transcript.pyannote[56].start |
197.53596875 |
transcript.pyannote[56].end |
197.58659375 |
transcript.pyannote[57].speaker |
SPEAKER_00 |
transcript.pyannote[57].start |
197.95784375 |
transcript.pyannote[57].end |
199.03784375 |
transcript.pyannote[58].speaker |
SPEAKER_00 |
transcript.pyannote[58].start |
200.50596875 |
transcript.pyannote[58].end |
201.13034375 |
transcript.pyannote[59].speaker |
SPEAKER_00 |
transcript.pyannote[59].start |
202.19346875 |
transcript.pyannote[59].end |
202.85159375 |
transcript.pyannote[60].speaker |
SPEAKER_00 |
transcript.pyannote[60].start |
203.18909375 |
transcript.pyannote[60].end |
204.89346875 |
transcript.pyannote[61].speaker |
SPEAKER_00 |
transcript.pyannote[61].start |
205.24784375 |
transcript.pyannote[61].end |
206.10846875 |
transcript.pyannote[62].speaker |
SPEAKER_00 |
transcript.pyannote[62].start |
206.66534375 |
transcript.pyannote[62].end |
208.60596875 |
transcript.pyannote[63].speaker |
SPEAKER_00 |
transcript.pyannote[63].start |
209.24721875 |
transcript.pyannote[63].end |
211.15409375 |
transcript.pyannote[64].speaker |
SPEAKER_00 |
transcript.pyannote[64].start |
211.60971875 |
transcript.pyannote[64].end |
212.50409375 |
transcript.pyannote[65].speaker |
SPEAKER_00 |
transcript.pyannote[65].start |
213.68534375 |
transcript.pyannote[65].end |
215.84534375 |
transcript.pyannote[66].speaker |
SPEAKER_00 |
transcript.pyannote[66].start |
216.60471875 |
transcript.pyannote[66].end |
218.44409375 |
transcript.pyannote[67].speaker |
SPEAKER_00 |
transcript.pyannote[67].start |
219.01784375 |
transcript.pyannote[67].end |
220.68846875 |
transcript.pyannote[68].speaker |
SPEAKER_00 |
transcript.pyannote[68].start |
222.27471875 |
transcript.pyannote[68].end |
224.97471875 |
transcript.pyannote[69].speaker |
SPEAKER_00 |
transcript.pyannote[69].start |
226.40909375 |
transcript.pyannote[69].end |
229.88534375 |
transcript.pyannote[70].speaker |
SPEAKER_00 |
transcript.pyannote[70].start |
230.44221875 |
transcript.pyannote[70].end |
233.19284375 |
transcript.pyannote[71].speaker |
SPEAKER_01 |
transcript.pyannote[71].start |
233.26034375 |
transcript.pyannote[71].end |
233.42909375 |
transcript.pyannote[72].speaker |
SPEAKER_00 |
transcript.pyannote[72].start |
234.08721875 |
transcript.pyannote[72].end |
235.50471875 |
transcript.pyannote[73].speaker |
SPEAKER_00 |
transcript.pyannote[73].start |
235.94346875 |
transcript.pyannote[73].end |
236.63534375 |
transcript.pyannote[74].speaker |
SPEAKER_00 |
transcript.pyannote[74].start |
236.87159375 |
transcript.pyannote[74].end |
237.34409375 |
transcript.pyannote[75].speaker |
SPEAKER_00 |
transcript.pyannote[75].start |
238.33971875 |
transcript.pyannote[75].end |
239.28471875 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
239.90909375 |
transcript.pyannote[76].end |
241.05659375 |
transcript.pyannote[77].speaker |
SPEAKER_00 |
transcript.pyannote[77].start |
242.01846875 |
transcript.pyannote[77].end |
244.66784375 |
transcript.pyannote[78].speaker |
SPEAKER_00 |
transcript.pyannote[78].start |
245.42721875 |
transcript.pyannote[78].end |
249.15659375 |
transcript.pyannote[79].speaker |
SPEAKER_00 |
transcript.pyannote[79].start |
249.57846875 |
transcript.pyannote[79].end |
251.02971875 |
transcript.pyannote[80].speaker |
SPEAKER_00 |
transcript.pyannote[80].start |
251.31659375 |
transcript.pyannote[80].end |
255.65346875 |
transcript.pyannote[81].speaker |
SPEAKER_00 |
transcript.pyannote[81].start |
256.32846875 |
transcript.pyannote[81].end |
258.20159375 |
transcript.pyannote[82].speaker |
SPEAKER_00 |
transcript.pyannote[82].start |
258.33659375 |
transcript.pyannote[82].end |
259.72034375 |
transcript.pyannote[83].speaker |
SPEAKER_00 |
transcript.pyannote[83].start |
260.51346875 |
transcript.pyannote[83].end |
261.17159375 |
transcript.pyannote[84].speaker |
SPEAKER_00 |
transcript.pyannote[84].start |
261.82971875 |
transcript.pyannote[84].end |
262.31909375 |
transcript.pyannote[85].speaker |
SPEAKER_00 |
transcript.pyannote[85].start |
263.12909375 |
transcript.pyannote[85].end |
268.12409375 |
transcript.pyannote[86].speaker |
SPEAKER_00 |
transcript.pyannote[86].start |
268.76534375 |
transcript.pyannote[86].end |
273.84471875 |
transcript.pyannote[87].speaker |
SPEAKER_00 |
transcript.pyannote[87].start |
274.51971875 |
transcript.pyannote[87].end |
275.14409375 |
transcript.pyannote[88].speaker |
SPEAKER_00 |
transcript.pyannote[88].start |
275.19471875 |
transcript.pyannote[88].end |
281.82659375 |
transcript.pyannote[89].speaker |
SPEAKER_00 |
transcript.pyannote[89].start |
281.97846875 |
transcript.pyannote[89].end |
283.54784375 |
transcript.pyannote[90].speaker |
SPEAKER_01 |
transcript.pyannote[90].start |
283.56471875 |
transcript.pyannote[90].end |
283.91909375 |
transcript.pyannote[91].speaker |
SPEAKER_00 |
transcript.pyannote[91].start |
283.96971875 |
transcript.pyannote[91].end |
284.98221875 |
transcript.pyannote[92].speaker |
SPEAKER_01 |
transcript.pyannote[92].start |
284.98221875 |
transcript.pyannote[92].end |
285.28596875 |
transcript.pyannote[93].speaker |
SPEAKER_00 |
transcript.pyannote[93].start |
285.48846875 |
transcript.pyannote[93].end |
290.02784375 |
transcript.pyannote[94].speaker |
SPEAKER_00 |
transcript.pyannote[94].start |
290.06159375 |
transcript.pyannote[94].end |
292.59284375 |
transcript.pyannote[95].speaker |
SPEAKER_00 |
transcript.pyannote[95].start |
293.40284375 |
transcript.pyannote[95].end |
293.92596875 |
transcript.pyannote[96].speaker |
SPEAKER_00 |
transcript.pyannote[96].start |
294.76971875 |
transcript.pyannote[96].end |
296.42346875 |
transcript.pyannote[97].speaker |
SPEAKER_00 |
transcript.pyannote[97].start |
297.48659375 |
transcript.pyannote[97].end |
298.56659375 |
transcript.pyannote[98].speaker |
SPEAKER_00 |
transcript.pyannote[98].start |
299.17409375 |
transcript.pyannote[98].end |
299.69721875 |
transcript.pyannote[99].speaker |
SPEAKER_00 |
transcript.pyannote[99].start |
301.45221875 |
transcript.pyannote[99].end |
302.51534375 |
transcript.pyannote[100].speaker |
SPEAKER_00 |
transcript.pyannote[100].start |
303.08909375 |
transcript.pyannote[100].end |
303.94971875 |
transcript.pyannote[101].speaker |
SPEAKER_00 |
transcript.pyannote[101].start |
303.96659375 |
transcript.pyannote[101].end |
303.98346875 |
transcript.pyannote[102].speaker |
SPEAKER_00 |
transcript.pyannote[102].start |
304.25346875 |
transcript.pyannote[102].end |
305.28284375 |
transcript.pyannote[103].speaker |
SPEAKER_00 |
transcript.pyannote[103].start |
305.60346875 |
transcript.pyannote[103].end |
311.29034375 |
transcript.pyannote[104].speaker |
SPEAKER_00 |
transcript.pyannote[104].start |
312.52221875 |
transcript.pyannote[104].end |
316.35284375 |
transcript.pyannote[105].speaker |
SPEAKER_00 |
transcript.pyannote[105].start |
316.94346875 |
transcript.pyannote[105].end |
320.82471875 |
transcript.pyannote[106].speaker |
SPEAKER_01 |
transcript.pyannote[106].start |
320.82471875 |
transcript.pyannote[106].end |
321.07784375 |
transcript.pyannote[107].speaker |
SPEAKER_00 |
transcript.pyannote[107].start |
321.07784375 |
transcript.pyannote[107].end |
324.25034375 |
transcript.pyannote[108].speaker |
SPEAKER_01 |
transcript.pyannote[108].start |
321.09471875 |
transcript.pyannote[108].end |
321.11159375 |
transcript.pyannote[109].speaker |
SPEAKER_00 |
transcript.pyannote[109].start |
324.58784375 |
transcript.pyannote[109].end |
327.05159375 |
transcript.pyannote[110].speaker |
SPEAKER_00 |
transcript.pyannote[110].start |
327.49034375 |
transcript.pyannote[110].end |
328.33409375 |
transcript.pyannote[111].speaker |
SPEAKER_00 |
transcript.pyannote[111].start |
329.26221875 |
transcript.pyannote[111].end |
332.67096875 |
transcript.pyannote[112].speaker |
SPEAKER_00 |
transcript.pyannote[112].start |
332.97471875 |
transcript.pyannote[112].end |
334.61159375 |
transcript.pyannote[113].speaker |
SPEAKER_00 |
transcript.pyannote[113].start |
334.99971875 |
transcript.pyannote[113].end |
335.57346875 |
transcript.pyannote[114].speaker |
SPEAKER_00 |
transcript.pyannote[114].start |
336.82221875 |
transcript.pyannote[114].end |
340.36596875 |
transcript.pyannote[115].speaker |
SPEAKER_00 |
transcript.pyannote[115].start |
340.75409375 |
transcript.pyannote[115].end |
342.86346875 |
transcript.pyannote[116].speaker |
SPEAKER_02 |
transcript.pyannote[116].start |
342.96471875 |
transcript.pyannote[116].end |
343.21784375 |
transcript.pyannote[117].speaker |
SPEAKER_00 |
transcript.pyannote[117].start |
344.24721875 |
transcript.pyannote[117].end |
345.93471875 |
transcript.pyannote[118].speaker |
SPEAKER_00 |
transcript.pyannote[118].start |
346.60971875 |
transcript.pyannote[118].end |
347.43659375 |
transcript.pyannote[119].speaker |
SPEAKER_00 |
transcript.pyannote[119].start |
348.16221875 |
transcript.pyannote[119].end |
349.09034375 |
transcript.pyannote[120].speaker |
SPEAKER_00 |
transcript.pyannote[120].start |
350.25471875 |
transcript.pyannote[120].end |
352.02659375 |
transcript.pyannote[121].speaker |
SPEAKER_00 |
transcript.pyannote[121].start |
352.87034375 |
transcript.pyannote[121].end |
353.66346875 |
transcript.pyannote[122].speaker |
SPEAKER_00 |
transcript.pyannote[122].start |
354.28784375 |
transcript.pyannote[122].end |
355.57034375 |
transcript.pyannote[123].speaker |
SPEAKER_00 |
transcript.pyannote[123].start |
355.94159375 |
transcript.pyannote[123].end |
356.83596875 |
transcript.pyannote[124].speaker |
SPEAKER_00 |
transcript.pyannote[124].start |
357.74721875 |
transcript.pyannote[124].end |
359.95784375 |
transcript.pyannote[125].speaker |
SPEAKER_00 |
transcript.pyannote[125].start |
360.31221875 |
transcript.pyannote[125].end |
361.24034375 |
transcript.pyannote[126].speaker |
SPEAKER_00 |
transcript.pyannote[126].start |
362.62409375 |
transcript.pyannote[126].end |
365.44221875 |
transcript.pyannote[127].speaker |
SPEAKER_00 |
transcript.pyannote[127].start |
366.35346875 |
transcript.pyannote[127].end |
368.58096875 |
transcript.pyannote[128].speaker |
SPEAKER_00 |
transcript.pyannote[128].start |
369.49221875 |
transcript.pyannote[128].end |
370.99409375 |
transcript.pyannote[129].speaker |
SPEAKER_00 |
transcript.pyannote[129].start |
371.53409375 |
transcript.pyannote[129].end |
374.03159375 |
transcript.pyannote[130].speaker |
SPEAKER_00 |
transcript.pyannote[130].start |
374.08221875 |
transcript.pyannote[130].end |
376.02284375 |
transcript.pyannote[131].speaker |
SPEAKER_01 |
transcript.pyannote[131].start |
376.10721875 |
transcript.pyannote[131].end |
376.37721875 |
transcript.pyannote[132].speaker |
SPEAKER_00 |
transcript.pyannote[132].start |
376.68096875 |
transcript.pyannote[132].end |
377.37284375 |
transcript.pyannote[133].speaker |
SPEAKER_00 |
transcript.pyannote[133].start |
378.35159375 |
transcript.pyannote[133].end |
379.92096875 |
transcript.pyannote[134].speaker |
SPEAKER_00 |
transcript.pyannote[134].start |
380.42721875 |
transcript.pyannote[134].end |
380.88284375 |
transcript.pyannote[135].speaker |
SPEAKER_00 |
transcript.pyannote[135].start |
381.60846875 |
transcript.pyannote[135].end |
383.51534375 |
transcript.pyannote[136].speaker |
SPEAKER_02 |
transcript.pyannote[136].start |
384.34221875 |
transcript.pyannote[136].end |
384.76409375 |
transcript.pyannote[137].speaker |
SPEAKER_02 |
transcript.pyannote[137].start |
385.10159375 |
transcript.pyannote[137].end |
392.30721875 |
transcript.pyannote[138].speaker |
SPEAKER_02 |
transcript.pyannote[138].start |
392.84721875 |
transcript.pyannote[138].end |
400.67721875 |
transcript.pyannote[139].speaker |
SPEAKER_00 |
transcript.pyannote[139].start |
393.48846875 |
transcript.pyannote[139].end |
393.52221875 |
transcript.pyannote[140].speaker |
SPEAKER_01 |
transcript.pyannote[140].start |
393.52221875 |
transcript.pyannote[140].end |
393.97784375 |
transcript.pyannote[141].speaker |
SPEAKER_00 |
transcript.pyannote[141].start |
393.97784375 |
transcript.pyannote[141].end |
394.26471875 |
transcript.pyannote[142].speaker |
SPEAKER_00 |
transcript.pyannote[142].start |
397.70721875 |
transcript.pyannote[142].end |
398.11221875 |
transcript.pyannote[143].speaker |
SPEAKER_00 |
transcript.pyannote[143].start |
400.67721875 |
transcript.pyannote[143].end |
400.76159375 |
transcript.pyannote[144].speaker |
SPEAKER_02 |
transcript.pyannote[144].start |
400.76159375 |
transcript.pyannote[144].end |
401.55471875 |
transcript.pyannote[145].speaker |
SPEAKER_00 |
transcript.pyannote[145].start |
400.77846875 |
transcript.pyannote[145].end |
408.18659375 |
transcript.pyannote[146].speaker |
SPEAKER_02 |
transcript.pyannote[146].start |
402.68534375 |
transcript.pyannote[146].end |
403.30971875 |
transcript.pyannote[147].speaker |
SPEAKER_01 |
transcript.pyannote[147].start |
403.30971875 |
transcript.pyannote[147].end |
403.74846875 |
transcript.pyannote[148].speaker |
SPEAKER_01 |
transcript.pyannote[148].start |
406.78596875 |
transcript.pyannote[148].end |
407.22471875 |
transcript.pyannote[149].speaker |
SPEAKER_01 |
transcript.pyannote[149].start |
408.33846875 |
transcript.pyannote[149].end |
408.76034375 |
transcript.pyannote[150].speaker |
SPEAKER_00 |
transcript.pyannote[150].start |
408.82784375 |
transcript.pyannote[150].end |
409.77284375 |
transcript.pyannote[151].speaker |
SPEAKER_00 |
transcript.pyannote[151].start |
409.89096875 |
transcript.pyannote[151].end |
410.04284375 |
transcript.pyannote[152].speaker |
SPEAKER_00 |
transcript.pyannote[152].start |
410.09346875 |
transcript.pyannote[152].end |
411.67971875 |
transcript.pyannote[153].speaker |
SPEAKER_00 |
transcript.pyannote[153].start |
412.20284375 |
transcript.pyannote[153].end |
413.40096875 |
transcript.pyannote[154].speaker |
SPEAKER_00 |
transcript.pyannote[154].start |
414.09284375 |
transcript.pyannote[154].end |
415.67909375 |
transcript.pyannote[155].speaker |
SPEAKER_02 |
transcript.pyannote[155].start |
415.67909375 |
transcript.pyannote[155].end |
416.33721875 |
transcript.pyannote[156].speaker |
SPEAKER_00 |
transcript.pyannote[156].start |
416.18534375 |
transcript.pyannote[156].end |
417.21471875 |
transcript.pyannote[157].speaker |
SPEAKER_02 |
transcript.pyannote[157].start |
416.67471875 |
transcript.pyannote[157].end |
418.71659375 |
transcript.pyannote[158].speaker |
SPEAKER_00 |
transcript.pyannote[158].start |
417.95721875 |
transcript.pyannote[158].end |
421.12971875 |
transcript.pyannote[159].speaker |
SPEAKER_02 |
transcript.pyannote[159].start |
418.96971875 |
transcript.pyannote[159].end |
422.37846875 |
transcript.pyannote[160].speaker |
SPEAKER_00 |
transcript.pyannote[160].start |
422.37846875 |
transcript.pyannote[160].end |
425.24721875 |
transcript.pyannote[161].speaker |
SPEAKER_02 |
transcript.pyannote[161].start |
425.09534375 |
transcript.pyannote[161].end |
425.55096875 |
transcript.pyannote[162].speaker |
SPEAKER_00 |
transcript.pyannote[162].start |
425.73659375 |
transcript.pyannote[162].end |
428.58846875 |
transcript.pyannote[163].speaker |
SPEAKER_01 |
transcript.pyannote[163].start |
428.63909375 |
transcript.pyannote[163].end |
428.90909375 |
transcript.pyannote[164].speaker |
SPEAKER_00 |
transcript.pyannote[164].start |
428.92596875 |
transcript.pyannote[164].end |
430.25909375 |
transcript.pyannote[165].speaker |
SPEAKER_00 |
transcript.pyannote[165].start |
430.39409375 |
transcript.pyannote[165].end |
435.22034375 |
transcript.pyannote[166].speaker |
SPEAKER_01 |
transcript.pyannote[166].start |
431.72721875 |
transcript.pyannote[166].end |
432.09846875 |
transcript.pyannote[167].speaker |
SPEAKER_01 |
transcript.pyannote[167].start |
433.88721875 |
transcript.pyannote[167].end |
433.90409375 |
transcript.pyannote[168].speaker |
SPEAKER_02 |
transcript.pyannote[168].start |
433.90409375 |
transcript.pyannote[168].end |
434.69721875 |
transcript.pyannote[169].speaker |
SPEAKER_00 |
transcript.pyannote[169].start |
435.62534375 |
transcript.pyannote[169].end |
436.18221875 |
transcript.pyannote[170].speaker |
SPEAKER_02 |
transcript.pyannote[170].start |
437.07659375 |
transcript.pyannote[170].end |
437.97096875 |
transcript.pyannote[171].speaker |
SPEAKER_02 |
transcript.pyannote[171].start |
438.62909375 |
transcript.pyannote[171].end |
440.02971875 |
transcript.pyannote[172].speaker |
SPEAKER_02 |
transcript.pyannote[172].start |
441.76784375 |
transcript.pyannote[172].end |
444.85596875 |
transcript.pyannote[173].speaker |
SPEAKER_00 |
transcript.pyannote[173].start |
443.30346875 |
transcript.pyannote[173].end |
443.82659375 |
transcript.pyannote[174].speaker |
SPEAKER_00 |
transcript.pyannote[174].start |
444.48471875 |
transcript.pyannote[174].end |
446.29034375 |
transcript.pyannote[175].speaker |
SPEAKER_02 |
transcript.pyannote[175].start |
445.31159375 |
transcript.pyannote[175].end |
446.81346875 |
transcript.pyannote[176].speaker |
SPEAKER_00 |
transcript.pyannote[176].start |
446.81346875 |
transcript.pyannote[176].end |
449.47971875 |
transcript.pyannote[177].speaker |
SPEAKER_00 |
transcript.pyannote[177].start |
449.91846875 |
transcript.pyannote[177].end |
456.02721875 |
transcript.pyannote[178].speaker |
SPEAKER_00 |
transcript.pyannote[178].start |
456.93846875 |
transcript.pyannote[178].end |
460.63409375 |
transcript.pyannote[179].speaker |
SPEAKER_01 |
transcript.pyannote[179].start |
460.39784375 |
transcript.pyannote[179].end |
461.03909375 |
transcript.pyannote[180].speaker |
SPEAKER_00 |
transcript.pyannote[180].start |
461.03909375 |
transcript.pyannote[180].end |
466.60784375 |
transcript.pyannote[181].speaker |
SPEAKER_00 |
transcript.pyannote[181].start |
467.31659375 |
transcript.pyannote[181].end |
469.22346875 |
transcript.pyannote[182].speaker |
SPEAKER_00 |
transcript.pyannote[182].start |
470.06721875 |
transcript.pyannote[182].end |
472.51409375 |
transcript.pyannote[183].speaker |
SPEAKER_02 |
transcript.pyannote[183].start |
473.30721875 |
transcript.pyannote[183].end |
473.54346875 |
transcript.pyannote[184].speaker |
SPEAKER_00 |
transcript.pyannote[184].start |
474.01596875 |
transcript.pyannote[184].end |
474.50534375 |
transcript.pyannote[185].speaker |
SPEAKER_00 |
transcript.pyannote[185].start |
475.09596875 |
transcript.pyannote[185].end |
476.29409375 |
transcript.pyannote[186].speaker |
SPEAKER_00 |
transcript.pyannote[186].start |
476.74971875 |
transcript.pyannote[186].end |
480.47909375 |
transcript.pyannote[187].speaker |
SPEAKER_01 |
transcript.pyannote[187].start |
480.71534375 |
transcript.pyannote[187].end |
480.73221875 |
transcript.pyannote[188].speaker |
SPEAKER_02 |
transcript.pyannote[188].start |
480.73221875 |
transcript.pyannote[188].end |
480.98534375 |
transcript.pyannote[189].speaker |
SPEAKER_01 |
transcript.pyannote[189].start |
480.98534375 |
transcript.pyannote[189].end |
481.00221875 |
transcript.pyannote[190].speaker |
SPEAKER_00 |
transcript.pyannote[190].start |
481.13721875 |
transcript.pyannote[190].end |
484.07346875 |
transcript.pyannote[191].speaker |
SPEAKER_00 |
transcript.pyannote[191].start |
484.25909375 |
transcript.pyannote[191].end |
486.06471875 |
transcript.pyannote[192].speaker |
SPEAKER_02 |
transcript.pyannote[192].start |
486.68909375 |
transcript.pyannote[192].end |
490.63784375 |
transcript.pyannote[193].speaker |
SPEAKER_02 |
transcript.pyannote[193].start |
490.65471875 |
transcript.pyannote[193].end |
490.70534375 |
transcript.pyannote[194].speaker |
SPEAKER_00 |
transcript.pyannote[194].start |
490.70534375 |
transcript.pyannote[194].end |
493.87784375 |
transcript.pyannote[195].speaker |
SPEAKER_02 |
transcript.pyannote[195].start |
491.27909375 |
transcript.pyannote[195].end |
492.54471875 |
transcript.pyannote[196].speaker |
SPEAKER_00 |
transcript.pyannote[196].start |
498.55221875 |
transcript.pyannote[196].end |
501.40409375 |
transcript.pyannote[197].speaker |
SPEAKER_02 |
transcript.pyannote[197].start |
501.40409375 |
transcript.pyannote[197].end |
501.69096875 |
transcript.pyannote[198].speaker |
SPEAKER_00 |
transcript.pyannote[198].start |
501.62346875 |
transcript.pyannote[198].end |
503.27721875 |
transcript.pyannote[199].speaker |
SPEAKER_02 |
transcript.pyannote[199].start |
503.22659375 |
transcript.pyannote[199].end |
505.96034375 |
transcript.pyannote[200].speaker |
SPEAKER_00 |
transcript.pyannote[200].start |
503.42909375 |
transcript.pyannote[200].end |
504.55971875 |
transcript.pyannote[201].speaker |
SPEAKER_00 |
transcript.pyannote[201].start |
505.03221875 |
transcript.pyannote[201].end |
515.08971875 |
transcript.pyannote[202].speaker |
SPEAKER_00 |
transcript.pyannote[202].start |
515.93346875 |
transcript.pyannote[202].end |
519.37596875 |
transcript.pyannote[203].speaker |
SPEAKER_00 |
transcript.pyannote[203].start |
519.56159375 |
transcript.pyannote[203].end |
522.09284375 |
transcript.pyannote[204].speaker |
SPEAKER_00 |
transcript.pyannote[204].start |
522.49784375 |
transcript.pyannote[204].end |
523.61159375 |
transcript.pyannote[205].speaker |
SPEAKER_00 |
transcript.pyannote[205].start |
523.96596875 |
transcript.pyannote[205].end |
525.94034375 |
transcript.pyannote[206].speaker |
SPEAKER_01 |
transcript.pyannote[206].start |
526.22721875 |
transcript.pyannote[206].end |
526.54784375 |
transcript.pyannote[207].speaker |
SPEAKER_00 |
transcript.pyannote[207].start |
526.96971875 |
transcript.pyannote[207].end |
528.53909375 |
transcript.pyannote[208].speaker |
SPEAKER_01 |
transcript.pyannote[208].start |
527.79659375 |
transcript.pyannote[208].end |
528.26909375 |
transcript.pyannote[209].speaker |
SPEAKER_00 |
transcript.pyannote[209].start |
528.94409375 |
transcript.pyannote[209].end |
529.53471875 |
transcript.pyannote[210].speaker |
SPEAKER_00 |
transcript.pyannote[210].start |
529.92284375 |
transcript.pyannote[210].end |
531.50909375 |
transcript.pyannote[211].speaker |
SPEAKER_00 |
transcript.pyannote[211].start |
532.09971875 |
transcript.pyannote[211].end |
535.76159375 |
transcript.pyannote[212].speaker |
SPEAKER_00 |
transcript.pyannote[212].start |
536.33534375 |
transcript.pyannote[212].end |
540.53721875 |
transcript.pyannote[213].speaker |
SPEAKER_00 |
transcript.pyannote[213].start |
541.04346875 |
transcript.pyannote[213].end |
545.04284375 |
transcript.pyannote[214].speaker |
SPEAKER_00 |
transcript.pyannote[214].start |
547.47284375 |
transcript.pyannote[214].end |
549.09284375 |
transcript.pyannote[215].speaker |
SPEAKER_02 |
transcript.pyannote[215].start |
548.36721875 |
transcript.pyannote[215].end |
549.44721875 |
transcript.pyannote[216].speaker |
SPEAKER_02 |
transcript.pyannote[216].start |
549.75096875 |
transcript.pyannote[216].end |
552.95721875 |
transcript.pyannote[217].speaker |
SPEAKER_02 |
transcript.pyannote[217].start |
553.15971875 |
transcript.pyannote[217].end |
553.21034375 |
transcript.pyannote[218].speaker |
SPEAKER_00 |
transcript.pyannote[218].start |
553.21034375 |
transcript.pyannote[218].end |
557.17596875 |
transcript.pyannote[219].speaker |
SPEAKER_02 |
transcript.pyannote[219].start |
553.22721875 |
transcript.pyannote[219].end |
553.78409375 |
transcript.pyannote[220].speaker |
SPEAKER_02 |
transcript.pyannote[220].start |
554.35784375 |
transcript.pyannote[220].end |
554.47596875 |
transcript.pyannote[221].speaker |
SPEAKER_02 |
transcript.pyannote[221].start |
556.29846875 |
transcript.pyannote[221].end |
561.32721875 |
transcript.pyannote[222].speaker |
SPEAKER_00 |
transcript.pyannote[222].start |
561.49596875 |
transcript.pyannote[222].end |
561.51284375 |
transcript.pyannote[223].speaker |
SPEAKER_01 |
transcript.pyannote[223].start |
561.51284375 |
transcript.pyannote[223].end |
561.95159375 |
transcript.pyannote[224].speaker |
SPEAKER_02 |
transcript.pyannote[224].start |
561.95159375 |
transcript.pyannote[224].end |
569.56221875 |
transcript.pyannote[225].speaker |
SPEAKER_02 |
transcript.pyannote[225].start |
570.35534375 |
transcript.pyannote[225].end |
574.45596875 |
transcript.pyannote[226].speaker |
SPEAKER_02 |
transcript.pyannote[226].start |
575.06346875 |
transcript.pyannote[226].end |
579.61971875 |
transcript.pyannote[227].speaker |
SPEAKER_02 |
transcript.pyannote[227].start |
580.09221875 |
transcript.pyannote[227].end |
584.98596875 |
transcript.pyannote[228].speaker |
SPEAKER_02 |
transcript.pyannote[228].start |
585.64409375 |
transcript.pyannote[228].end |
595.04346875 |
transcript.pyannote[229].speaker |
SPEAKER_00 |
transcript.pyannote[229].start |
595.04346875 |
transcript.pyannote[229].end |
603.48096875 |
transcript.pyannote[230].speaker |
SPEAKER_02 |
transcript.pyannote[230].start |
595.61721875 |
transcript.pyannote[230].end |
596.12346875 |
transcript.pyannote[231].speaker |
SPEAKER_02 |
transcript.pyannote[231].start |
597.57471875 |
transcript.pyannote[231].end |
599.46471875 |
transcript.pyannote[232].speaker |
SPEAKER_00 |
transcript.pyannote[232].start |
603.86909375 |
transcript.pyannote[232].end |
611.32784375 |
transcript.pyannote[233].speaker |
SPEAKER_01 |
transcript.pyannote[233].start |
608.34096875 |
transcript.pyannote[233].end |
608.71221875 |
transcript.pyannote[234].speaker |
SPEAKER_01 |
transcript.pyannote[234].start |
609.69096875 |
transcript.pyannote[234].end |
610.04534375 |
transcript.pyannote[235].speaker |
SPEAKER_00 |
transcript.pyannote[235].start |
611.81721875 |
transcript.pyannote[235].end |
633.46784375 |
transcript.pyannote[236].speaker |
SPEAKER_02 |
transcript.pyannote[236].start |
632.06721875 |
transcript.pyannote[236].end |
632.26971875 |
transcript.pyannote[237].speaker |
SPEAKER_02 |
transcript.pyannote[237].start |
633.31596875 |
transcript.pyannote[237].end |
637.41659375 |
transcript.pyannote[238].speaker |
SPEAKER_00 |
transcript.pyannote[238].start |
634.15971875 |
transcript.pyannote[238].end |
634.71659375 |
transcript.pyannote[239].speaker |
SPEAKER_00 |
transcript.pyannote[239].start |
635.13846875 |
transcript.pyannote[239].end |
637.53471875 |
transcript.pyannote[240].speaker |
SPEAKER_02 |
transcript.pyannote[240].start |
637.77096875 |
transcript.pyannote[240].end |
639.27284375 |
transcript.pyannote[241].speaker |
SPEAKER_00 |
transcript.pyannote[241].start |
637.87221875 |
transcript.pyannote[241].end |
645.53346875 |
transcript.pyannote[242].speaker |
SPEAKER_01 |
transcript.pyannote[242].start |
639.27284375 |
transcript.pyannote[242].end |
639.45846875 |
transcript.pyannote[243].speaker |
SPEAKER_02 |
transcript.pyannote[243].start |
640.03221875 |
transcript.pyannote[243].end |
640.35284375 |
transcript.pyannote[244].speaker |
SPEAKER_01 |
transcript.pyannote[244].start |
640.35284375 |
transcript.pyannote[244].end |
640.36971875 |
transcript.pyannote[245].speaker |
SPEAKER_00 |
transcript.pyannote[245].start |
646.00596875 |
transcript.pyannote[245].end |
646.68096875 |
transcript.pyannote[246].speaker |
SPEAKER_00 |
transcript.pyannote[246].start |
646.79909375 |
transcript.pyannote[246].end |
650.66346875 |
transcript.pyannote[247].speaker |
SPEAKER_00 |
transcript.pyannote[247].start |
650.95034375 |
transcript.pyannote[247].end |
651.52409375 |
transcript.pyannote[248].speaker |
SPEAKER_00 |
transcript.pyannote[248].start |
652.80659375 |
transcript.pyannote[248].end |
654.93284375 |
transcript.pyannote[249].speaker |
SPEAKER_00 |
transcript.pyannote[249].start |
655.55721875 |
transcript.pyannote[249].end |
656.24909375 |
transcript.pyannote[250].speaker |
SPEAKER_00 |
transcript.pyannote[250].start |
656.97471875 |
transcript.pyannote[250].end |
665.68221875 |
transcript.pyannote[251].speaker |
SPEAKER_01 |
transcript.pyannote[251].start |
658.52721875 |
transcript.pyannote[251].end |
658.67909375 |
transcript.pyannote[252].speaker |
SPEAKER_02 |
transcript.pyannote[252].start |
658.67909375 |
transcript.pyannote[252].end |
659.06721875 |
transcript.pyannote[253].speaker |
SPEAKER_02 |
transcript.pyannote[253].start |
665.15909375 |
transcript.pyannote[253].end |
665.37846875 |
transcript.pyannote[254].speaker |
SPEAKER_02 |
transcript.pyannote[254].start |
665.68221875 |
transcript.pyannote[254].end |
665.85096875 |
transcript.pyannote[255].speaker |
SPEAKER_00 |
transcript.pyannote[255].start |
665.85096875 |
transcript.pyannote[255].end |
667.94346875 |
transcript.pyannote[256].speaker |
SPEAKER_02 |
transcript.pyannote[256].start |
666.25596875 |
transcript.pyannote[256].end |
666.62721875 |
transcript.pyannote[257].speaker |
SPEAKER_01 |
transcript.pyannote[257].start |
666.62721875 |
transcript.pyannote[257].end |
666.64409375 |
transcript.pyannote[258].speaker |
SPEAKER_02 |
transcript.pyannote[258].start |
667.52159375 |
transcript.pyannote[258].end |
667.70721875 |
transcript.pyannote[259].speaker |
SPEAKER_01 |
transcript.pyannote[259].start |
667.70721875 |
transcript.pyannote[259].end |
667.77471875 |
transcript.pyannote[260].speaker |
SPEAKER_01 |
transcript.pyannote[260].start |
669.07409375 |
transcript.pyannote[260].end |
669.96846875 |
transcript.whisperx[0].start |
6.341 |
transcript.whisperx[0].end |
33.922 |
transcript.whisperx[0].text |
謝謝主席。主席請一下許部長。請許部長。兩位委員好。部長好。部長我看...部長我看今天的業務報告,就有關年金改革的準備的部分,部裡面這邊還是一直停留在收集意見。 |
transcript.whisperx[1].start |
35.578 |
transcript.whisperx[1].end |
62.205 |
transcript.whisperx[1].text |
對不對我看你們的給我報告收集意見跟溝通會不會會不會收集意見跟溝通的時間太長了部長不是我不是不是不是我我我知道這是一項很很嚴峻的工程我也不是想為難你可是因為我覺得好像每每一次 |
transcript.whisperx[2].start |
63.615 |
transcript.whisperx[2].end |
88.172 |
transcript.whisperx[2].text |
每一次的業務報告有關年改的部分大概一直都是停留在收集意見跟評估那這樣子到底年改革什麼時候可以啟動什麼時候可以落實讓讓讓廣大的勞工可以得到安心到底什麼時候 |
transcript.whisperx[3].start |
89.434 |
transcript.whisperx[3].end |
102.879 |
transcript.whisperx[3].text |
委員這個期程部分我們會來通盤的規劃只是說因為不是 現在部長我打岔一下部長我打岔一下就是說你假如說說今天來EO報告已經有期程 |
transcript.whisperx[4].start |
104.147 |
transcript.whisperx[4].end |
126.414 |
transcript.whisperx[4].text |
那我可能還可以接受可是這6年來我看部長也已經認滿6年了這個是一個非常長壽的部長可是對於跟勞工這麼息息相關影響這麼重大的一個政策一直停留在 |
transcript.whisperx[5].start |
128.234 |
transcript.whisperx[5].end |
136.29 |
transcript.whisperx[5].text |
在準備跟收集意見達到共識這個階段本席真的沒有辦法接受 |
transcript.whisperx[6].start |
137.871 |
transcript.whisperx[6].end |
165.084 |
transcript.whisperx[6].text |
謝謝委員因為這部分的確是不容易因為勞工的人口數實在是太多每個產業勞工職業勞工的意見都不同關心的點都不同所以這個部分我也認為說這個其實應該要更我曾經在委員會跟部長討論過我覺得任何一項改革都不可能有共識 |
transcript.whisperx[7].start |
166.547 |
transcript.whisperx[7].end |
186.378 |
transcript.whisperx[7].text |
吼都不可能有共識那我也知道欸勞工的的年齡改革為什麼困難就是因為他原本的的可以領到的給付就少那欸廣大的勞工也沒的受薪階級也沒有因為台灣的經濟成長的 |
transcript.whisperx[8].start |
190.575 |
transcript.whisperx[8].end |
212.078 |
transcript.whisperx[8].text |
他的薪資等比例的增加所以要增加保費也有一定的阻力那要延後退可能會引發很大的風波所以我知道困難在哪裡可是也正因為困難所以才 |
transcript.whisperx[9].start |
214.275 |
transcript.whisperx[9].end |
240.851 |
transcript.whisperx[9].text |
選民給民進黨機會就是要民進黨面對困難我還記得我們在從事軍功校年改的時候整個民進黨黨團大概受影響最大的就是我因為我澎湖的軍功校比例太高了可是我還是帶著鋼盔挺過了年改 |
transcript.whisperx[10].start |
242.479 |
transcript.whisperx[10].end |
263.187 |
transcript.whisperx[10].text |
我也已經又當選兩屆了就是說應該像蔡英文總統講的就是應該要改革的就是必須要改革必須要想到一套方案出來讓退休的不恐懼讓正在繳保費的喜難這個是我們的責任 |
transcript.whisperx[11].start |
268.891 |
transcript.whisperx[11].end |
296.103 |
transcript.whisperx[11].text |
那我看這幾年就是提撥成為改革唯一的選項那這個本席也不反對甚至於我也已經提案把政府負擔最終的責任入法為什麼我這麼重視這件事情就是我講的這必須要讓勞動者有一個安定的心情 |
transcript.whisperx[12].start |
297.943 |
transcript.whisperx[12].end |
315.65 |
transcript.whisperx[12].text |
欸讓他知道知道任何人執政都不會放棄這一千多萬的老公朋友這一千多萬對台灣經濟有卓著貢獻的老公我我我 |
transcript.whisperx[13].start |
317.702 |
transcript.whisperx[13].end |
342.232 |
transcript.whisperx[13].text |
我覺得我們必須要去面對現在就是這樣子就我剛才講的我知道改革的困難為什麼呢因為不要說減少給付就以目前的給付來看我們目前在請領勞工給付的人數大概有174萬平均每個月 |
transcript.whisperx[14].start |
346.853 |
transcript.whisperx[14].end |
367.741 |
transcript.whisperx[14].text |
領到的是18000多18000多可是最低台灣的最低生活費以台北市來講就已經高達19000多其台北市以外的地方平均值也已經將近到達15000 |
transcript.whisperx[15].start |
369.554 |
transcript.whisperx[15].end |
383.083 |
transcript.whisperx[15].text |
那他現在領這樣子已經快要快要未達在臺北市已經未達未達最低生活費的標準了現在萬一再減少幾副怎麼辦 |
transcript.whisperx[16].start |
385.166 |
transcript.whisperx[16].end |
413.196 |
transcript.whisperx[16].text |
對,各位報告但是我們其實臺灣的產業勞工來看他其實他退休包括兩個一個就勞保另外一個就勞退這兩個加起來那當然還有一些健保啦長照現在是照顧我們的退休的人員健保跟長照是另外一回事啦我們就聚焦在勞工的部分就勞保跟勞退可是呢勞退的比例呢就是太低了 |
transcript.whisperx[17].start |
414.176 |
transcript.whisperx[17].end |
439.434 |
transcript.whisperx[17].text |
字體的部分太低了。字體比較低,但是固體拿到700多萬喔。大概是這樣子啦。前體體角數大概在106年的時候大概是14%多啦。那現在呢?就是到字體的部分。 |
transcript.whisperx[18].start |
441.823 |
transcript.whisperx[18].end |
464.872 |
transcript.whisperx[18].text |
我們到去年年底是14.17%人數是106萬所以就是像部長講的沒有錯勞工的退休的保障我們的設計是架構在勞保跟勞退可是問題是勞退本身有一個現象就這14點幾% |
transcript.whisperx[19].start |
467.352 |
transcript.whisperx[19].end |
493.67 |
transcript.whisperx[19].text |
他你你你仔細去看新知所得越高的越願意自提配合自提的部分那越低的呢因為他的所得本來就低所以他要再要再提出6%他可能有他的困難度不過我也還有一個固體6%固體6%是僱主一定要提撥的對我知道我知道那6%就是 |
transcript.whisperx[20].start |
495.811 |
transcript.whisperx[20].end |
497.858 |
transcript.whisperx[20].text |
響鈴 |
transcript.whisperx[21].start |
498.598 |
transcript.whisperx[21].end |
525.693 |
transcript.whisperx[21].text |
那6%呢是大家都有我現在講的是6加6特別是以薪資低的勞工來看6加6才足以保障他的退休生活那因為他假如說本來就低薪他可以領的勞保給付本來就低 |
transcript.whisperx[22].start |
527.011 |
transcript.whisperx[22].end |
544.592 |
transcript.whisperx[22].text |
然後呢他又因為職涯的過程生活的所需教養子女孝敬父母所以他可能要自提這六趴對他來講就馬上面臨生活的困頓 |
transcript.whisperx[23].start |
547.503 |
transcript.whisperx[23].end |
569.045 |
transcript.whisperx[23].text |
部長你懂我的意思嗎?我知道我知道不過當然啦如果是低薪的齁可能多數都是低薪的低薪的字題很少啦對我們現在大概有統計啦齁大概平均啦齁報告委員平均我們那個月投保薪資大概就是平均大概3萬7啦齁如果以3萬7來看喔他的勞保 |
transcript.whisperx[24].start |
570.564 |
transcript.whisperx[24].end |
583.476 |
transcript.whisperx[24].text |
應照按照現在限制他大概是領1萬7左右然後再如果他的再加上勞退就是固體只算固體不算自體啦齁大概1萬所以這個加起來勞保加勞退大概有27700 |
transcript.whisperx[25].start |
585.837 |
transcript.whisperx[25].end |
610.872 |
transcript.whisperx[25].text |
就是像一個退休勞工以平均的月頭保薪資來看如果是37000平均大概我們抓大概37000這樣領起來有27000多對啊這種平均值就是這種平均值就是比較看不到看不到真正弱勢的啦保障弱勢呢是民進黨邁向指正最重要的一個一個一個 |
transcript.whisperx[26].start |
611.732 |
transcript.whisperx[26].end |
637.619 |
transcript.whisperx[26].text |
對對對 |
transcript.whisperx[27].start |
638.319 |
transcript.whisperx[27].end |
649.526 |
transcript.whisperx[27].text |
我也知道很困難可是我常說不困難的事情怎麼輪得到我們做呢那不然我最後問一個問題就是 |
transcript.whisperx[28].start |
652.844 |
transcript.whisperx[28].end |
667.699 |
transcript.whisperx[28].text |
本席已經提出來政府擔負最終的支付責任的保證那這樣子的提案勞動部這邊的立場會支持嗎我們支持好謝謝部長謝謝主席謝謝楊耀文委員 |