iVOD / 165420

Field Value
IVOD_ID 165420
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/165420
日期 2025-11-13
會議資料.會議代碼 委員會-11-4-20-8
會議資料.會議代碼:str 第11屆第4會期財政委員會第8次全體委員會議
會議資料.屆 11
會議資料.會期 4
會議資料.會次 8
會議資料.種類 委員會
會議資料.委員會代碼[0] 20
會議資料.委員會代碼:str[0] 財政委員會
會議資料.標題 第11屆第4會期財政委員會第8次全體委員會議
影片種類 Clip
開始時間 2025-11-13T11:54:15+08:00
結束時間 2025-11-13T12:05:33+08:00
影片長度 00:11:18
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/fffa2c65c610face59a7ab60d9034949fa47f864c5dfb45a0834c22697b3aa2ad2e2cafc87676f955ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 顏寬恒
委員發言時間 11:54:15 - 12:05:33
會議時間 2025-11-13T09:00:00+08:00
會議名稱 立法院第11屆第4會期財政委員會第8次全體委員會議(事由:一、邀請財政部莊部長翠雲、行政院主計總處陳主計長淑姿、中央銀行副總裁、國家發展委員會葉主任委員俊顯、經濟部次長、勞動部次長、衛生福利部次長就「經濟成長讓全民共享:政府如何縮短所得差距暨改善相對貧窮化之對策」進行專題報告,並備質詢。 二、審查本院民進黨黨團擬具「財政收支劃分法第十六條之一未分配款運用暫行條例草案」案。)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 3.38909375
transcript.pyannote[0].end 7.54034375
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 7.89471875
transcript.pyannote[1].end 9.83534375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 10.34159375
transcript.pyannote[2].end 11.86034375
transcript.pyannote[3].speaker SPEAKER_04
transcript.pyannote[3].start 16.06221875
transcript.pyannote[3].end 16.60221875
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 16.90596875
transcript.pyannote[4].end 17.61471875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 18.27284375
transcript.pyannote[5].end 18.88034375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 19.63971875
transcript.pyannote[6].end 20.26409375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 20.38221875
transcript.pyannote[7].end 31.01346875
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 31.65471875
transcript.pyannote[8].end 37.18971875
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 37.45971875
transcript.pyannote[9].end 41.61096875
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 42.03284375
transcript.pyannote[10].end 51.49971875
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 51.93846875
transcript.pyannote[11].end 53.54159375
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 53.69346875
transcript.pyannote[12].end 64.62846875
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 64.91534375
transcript.pyannote[13].end 66.38346875
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 66.61971875
transcript.pyannote[14].end 67.34534375
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 68.25659375
transcript.pyannote[15].end 69.72471875
transcript.pyannote[16].speaker SPEAKER_04
transcript.pyannote[16].start 69.53909375
transcript.pyannote[16].end 75.71534375
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 76.57596875
transcript.pyannote[17].end 78.16221875
transcript.pyannote[18].speaker SPEAKER_04
transcript.pyannote[18].start 78.46596875
transcript.pyannote[18].end 85.55346875
transcript.pyannote[19].speaker SPEAKER_04
transcript.pyannote[19].start 85.65471875
transcript.pyannote[19].end 92.30346875
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 92.43846875
transcript.pyannote[20].end 94.12596875
transcript.pyannote[21].speaker SPEAKER_04
transcript.pyannote[21].start 94.15971875
transcript.pyannote[21].end 94.21034375
transcript.pyannote[22].speaker SPEAKER_05
transcript.pyannote[22].start 94.21034375
transcript.pyannote[22].end 94.32846875
transcript.pyannote[23].speaker SPEAKER_04
transcript.pyannote[23].start 94.32846875
transcript.pyannote[23].end 94.41284375
transcript.pyannote[24].speaker SPEAKER_04
transcript.pyannote[24].start 94.86846875
transcript.pyannote[24].end 94.90221875
transcript.pyannote[25].speaker SPEAKER_05
transcript.pyannote[25].start 94.90221875
transcript.pyannote[25].end 123.97784375
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 123.64034375
transcript.pyannote[26].end 141.35909375
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 141.51096875
transcript.pyannote[27].end 151.28159375
transcript.pyannote[28].speaker SPEAKER_04
transcript.pyannote[28].start 151.28159375
transcript.pyannote[28].end 154.89284375
transcript.pyannote[29].speaker SPEAKER_01
transcript.pyannote[29].start 154.77471875
transcript.pyannote[29].end 156.09096875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 157.27221875
transcript.pyannote[30].end 160.12409375
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 161.23784375
transcript.pyannote[31].end 163.19534375
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 163.19534375
transcript.pyannote[32].end 164.41034375
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 166.97534375
transcript.pyannote[33].end 169.15221875
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 170.23221875
transcript.pyannote[34].end 173.16846875
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 173.67471875
transcript.pyannote[35].end 174.99096875
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 175.41284375
transcript.pyannote[36].end 178.01159375
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 178.33221875
transcript.pyannote[37].end 180.89721875
transcript.pyannote[38].speaker SPEAKER_05
transcript.pyannote[38].start 182.41596875
transcript.pyannote[38].end 184.66034375
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 184.76159375
transcript.pyannote[39].end 190.90409375
transcript.pyannote[40].speaker SPEAKER_05
transcript.pyannote[40].start 191.00534375
transcript.pyannote[40].end 197.56971875
transcript.pyannote[41].speaker SPEAKER_05
transcript.pyannote[41].start 201.56909375
transcript.pyannote[41].end 201.61971875
transcript.pyannote[42].speaker SPEAKER_05
transcript.pyannote[42].start 201.80534375
transcript.pyannote[42].end 202.02471875
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 203.08784375
transcript.pyannote[43].end 204.28596875
transcript.pyannote[44].speaker SPEAKER_05
transcript.pyannote[44].start 203.66159375
transcript.pyannote[44].end 205.99034375
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 206.27721875
transcript.pyannote[45].end 206.58096875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 209.34846875
transcript.pyannote[46].end 211.44096875
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 211.87971875
transcript.pyannote[47].end 215.72721875
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 217.34721875
transcript.pyannote[48].end 218.42721875
transcript.pyannote[49].speaker SPEAKER_05
transcript.pyannote[49].start 218.42721875
transcript.pyannote[49].end 218.47784375
transcript.pyannote[50].speaker SPEAKER_05
transcript.pyannote[50].start 219.32159375
transcript.pyannote[50].end 219.45659375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 219.45659375
transcript.pyannote[51].end 219.96284375
transcript.pyannote[52].speaker SPEAKER_05
transcript.pyannote[52].start 219.96284375
transcript.pyannote[52].end 220.50284375
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 220.50284375
transcript.pyannote[53].end 220.57034375
transcript.pyannote[54].speaker SPEAKER_05
transcript.pyannote[54].start 220.57034375
transcript.pyannote[54].end 220.60409375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 220.78971875
transcript.pyannote[55].end 222.69659375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 223.37159375
transcript.pyannote[56].end 224.19846875
transcript.pyannote[57].speaker SPEAKER_05
transcript.pyannote[57].start 223.55721875
transcript.pyannote[57].end 233.19284375
transcript.pyannote[58].speaker SPEAKER_05
transcript.pyannote[58].start 233.90159375
transcript.pyannote[58].end 234.22221875
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 235.52159375
transcript.pyannote[59].end 240.26346875
transcript.pyannote[60].speaker SPEAKER_05
transcript.pyannote[60].start 240.70221875
transcript.pyannote[60].end 245.42721875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 245.71409375
transcript.pyannote[61].end 250.86096875
transcript.pyannote[62].speaker SPEAKER_05
transcript.pyannote[62].start 247.46909375
transcript.pyannote[62].end 248.24534375
transcript.pyannote[63].speaker SPEAKER_05
transcript.pyannote[63].start 250.72596875
transcript.pyannote[63].end 265.35659375
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 251.14784375
transcript.pyannote[64].end 251.78909375
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 253.25721875
transcript.pyannote[65].end 254.13471875
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 262.96034375
transcript.pyannote[66].end 263.29784375
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 265.17096875
transcript.pyannote[67].end 270.90846875
transcript.pyannote[68].speaker SPEAKER_05
transcript.pyannote[68].start 271.07721875
transcript.pyannote[68].end 273.65909375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 273.65909375
transcript.pyannote[69].end 281.26971875
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 281.69159375
transcript.pyannote[70].end 282.24846875
transcript.pyannote[71].speaker SPEAKER_05
transcript.pyannote[71].start 281.87721875
transcript.pyannote[71].end 290.44971875
transcript.pyannote[72].speaker SPEAKER_05
transcript.pyannote[72].start 290.82096875
transcript.pyannote[72].end 290.83784375
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 290.83784375
transcript.pyannote[73].end 300.62534375
transcript.pyannote[74].speaker SPEAKER_05
transcript.pyannote[74].start 290.85471875
transcript.pyannote[74].end 290.97284375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 301.14846875
transcript.pyannote[75].end 302.07659375
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 302.51534375
transcript.pyannote[76].end 306.44721875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 307.03784375
transcript.pyannote[77].end 307.52721875
transcript.pyannote[78].speaker SPEAKER_05
transcript.pyannote[78].start 307.42596875
transcript.pyannote[78].end 307.49346875
transcript.pyannote[79].speaker SPEAKER_05
transcript.pyannote[79].start 307.52721875
transcript.pyannote[79].end 311.91471875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 311.45909375
transcript.pyannote[80].end 322.96784375
transcript.pyannote[81].speaker SPEAKER_05
transcript.pyannote[81].start 321.90471875
transcript.pyannote[81].end 328.67159375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 328.67159375
transcript.pyannote[82].end 331.38846875
transcript.pyannote[83].speaker SPEAKER_05
transcript.pyannote[83].start 331.01721875
transcript.pyannote[83].end 331.33784375
transcript.pyannote[84].speaker SPEAKER_05
transcript.pyannote[84].start 331.38846875
transcript.pyannote[84].end 336.14721875
transcript.pyannote[85].speaker SPEAKER_05
transcript.pyannote[85].start 336.55221875
transcript.pyannote[85].end 342.03659375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 341.66534375
transcript.pyannote[86].end 344.80409375
transcript.pyannote[87].speaker SPEAKER_05
transcript.pyannote[87].start 344.80409375
transcript.pyannote[87].end 344.97284375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 344.97284375
transcript.pyannote[88].end 350.59221875
transcript.pyannote[89].speaker SPEAKER_05
transcript.pyannote[89].start 350.92971875
transcript.pyannote[89].end 355.51971875
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 356.31284375
transcript.pyannote[90].end 359.01284375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 359.46846875
transcript.pyannote[91].end 376.56284375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 377.06909375
transcript.pyannote[92].end 378.26721875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 378.94221875
transcript.pyannote[93].end 380.79846875
transcript.pyannote[94].speaker SPEAKER_05
transcript.pyannote[94].start 380.76471875
transcript.pyannote[94].end 380.78159375
transcript.pyannote[95].speaker SPEAKER_05
transcript.pyannote[95].start 380.79846875
transcript.pyannote[95].end 400.40721875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 384.74721875
transcript.pyannote[96].end 385.16909375
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 401.58846875
transcript.pyannote[97].end 403.71471875
transcript.pyannote[98].speaker SPEAKER_05
transcript.pyannote[98].start 403.68096875
transcript.pyannote[98].end 403.69784375
transcript.pyannote[99].speaker SPEAKER_05
transcript.pyannote[99].start 403.71471875
transcript.pyannote[99].end 403.81596875
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 405.84096875
transcript.pyannote[100].end 406.85346875
transcript.pyannote[101].speaker SPEAKER_03
transcript.pyannote[101].start 408.49034375
transcript.pyannote[101].end 408.99659375
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 409.55346875
transcript.pyannote[102].end 410.27909375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 410.66721875
transcript.pyannote[103].end 440.02971875
transcript.pyannote[104].speaker SPEAKER_01
transcript.pyannote[104].start 440.31659375
transcript.pyannote[104].end 455.28471875
transcript.pyannote[105].speaker SPEAKER_03
transcript.pyannote[105].start 455.43659375
transcript.pyannote[105].end 488.84909375
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 461.59596875
transcript.pyannote[106].end 461.95034375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 488.96721875
transcript.pyannote[107].end 492.98346875
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 493.28721875
transcript.pyannote[108].end 497.33721875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 497.86034375
transcript.pyannote[109].end 505.90971875
transcript.pyannote[110].speaker SPEAKER_03
transcript.pyannote[110].start 505.90971875
transcript.pyannote[110].end 507.46221875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 506.44971875
transcript.pyannote[111].end 509.85846875
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 510.53346875
transcript.pyannote[112].end 512.08596875
transcript.pyannote[113].speaker SPEAKER_00
transcript.pyannote[113].start 521.97471875
transcript.pyannote[113].end 522.95346875
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 523.84784375
transcript.pyannote[114].end 525.02909375
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 525.07971875
transcript.pyannote[115].end 525.53534375
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 529.92284375
transcript.pyannote[116].end 530.58096875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 532.80846875
transcript.pyannote[117].end 533.87159375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 534.95159375
transcript.pyannote[118].end 535.91346875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 537.28034375
transcript.pyannote[119].end 552.73784375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 553.07534375
transcript.pyannote[120].end 555.45471875
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 555.57284375
transcript.pyannote[121].end 558.82971875
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 559.04909375
transcript.pyannote[122].end 560.44971875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 560.56784375
transcript.pyannote[123].end 563.47034375
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 563.92596875
transcript.pyannote[124].end 564.36471875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 564.55034375
transcript.pyannote[125].end 568.12784375
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 569.07284375
transcript.pyannote[126].end 573.91596875
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 574.21971875
transcript.pyannote[127].end 579.94034375
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 580.91909375
transcript.pyannote[128].end 585.44159375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 584.15909375
transcript.pyannote[129].end 584.32784375
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 585.67784375
transcript.pyannote[130].end 588.81659375
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 588.34409375
transcript.pyannote[131].end 590.40284375
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 591.66846875
transcript.pyannote[132].end 596.84909375
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 598.08096875
transcript.pyannote[133].end 608.99909375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 610.12971875
transcript.pyannote[134].end 610.50096875
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 611.63159375
transcript.pyannote[135].end 615.59721875
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 615.96846875
transcript.pyannote[136].end 617.60534375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 618.43221875
transcript.pyannote[137].end 618.98909375
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 620.08596875
transcript.pyannote[138].end 624.86159375
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 624.94596875
transcript.pyannote[139].end 637.80471875
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 638.47971875
transcript.pyannote[140].end 645.02721875
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 645.41534375
transcript.pyannote[141].end 652.19909375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 652.78971875
transcript.pyannote[142].end 653.32971875
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 654.27471875
transcript.pyannote[143].end 654.83159375
transcript.pyannote[144].speaker SPEAKER_01
transcript.pyannote[144].start 654.96659375
transcript.pyannote[144].end 655.00034375
transcript.pyannote[145].speaker SPEAKER_01
transcript.pyannote[145].start 655.18596875
transcript.pyannote[145].end 661.42971875
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 661.51409375
transcript.pyannote[146].end 662.34096875
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 662.34096875
transcript.pyannote[147].end 667.77471875
transcript.whisperx[0].start 3.653
transcript.whisperx[0].end 9.638
transcript.whisperx[0].text 主席各位烈士官員大家早主席有請財政部莊部長主席處陳主席長來請莊部長陳主席長委員好
transcript.whisperx[1].start 17.109
transcript.whisperx[1].end 35.246
transcript.whisperx[1].text 部長好 主委長吉林係數是國際間最常用來衡量財富分配比較均衡程度的統計指標產生部最新公布的資料台灣112年每戶吉林係數是0.339每年每人係數是0.272
transcript.whisperx[2].start 42.153
transcript.whisperx[2].end 59.39
transcript.whisperx[2].text 但這個數據保持一個懷疑的態度110年主計總數公布的數據台灣吉尼系數是0.606那短短的兩三年這個系數突然縮小到0.339根本是不可能的
transcript.whisperx[3].start 59.91
transcript.whisperx[3].end 74.845
transcript.whisperx[3].text 那主席長還有部長可不可以分別跟我們說明一下你們各自的算法是怎麼算不然為什麼差距這麼大無法理解是部長先相關的數據財政部長基本上都是依據主席總書的公告因為這是有主席總書的權責不好意思再說一下
transcript.whisperx[4].start 78.55
transcript.whisperx[4].end 93.806
transcript.whisperx[4].text 也就是說相關的數據這些所得都是我們是根據主計總處這邊所公布的資料那在8月15號的時候他也相關也有相關的公告我想這個部分跟委員做這樣的一個說明好那請主席講
transcript.whisperx[5].start 95.189
transcript.whisperx[5].end 121.606
transcript.whisperx[5].text 跟委員報告因為剛剛您講的那個0.606是屬於財富的部分有包括家庭財富所得的部分那這個部分是我們每個家戶所得的一個分配情形113年度的經理係數是0.341加每戶的部分那每人的部分是0.277這個部分那如果說是五等分的差別倍數就是3.92這個部分
transcript.whisperx[6].start 123.667
transcript.whisperx[6].end 150.925
transcript.whisperx[6].text 不是 那兩者就是說剛剛部長你說是依照主席總書提供的資料去做這個計算那你要清楚的說明啊不然說民眾看到這些數據誤以為說我國的貧富差距會有改善事實上沒有改善嘛 對不對從75倍到150倍貧富差距那麼大然後用這樣子的一個數據沒有清楚的說明造成誤解那透明的數據解釋對於提高民眾的信任跟理解是非常重要的好不好 部長
transcript.whisperx[7].start 151.345
transcript.whisperx[7].end 180.607
transcript.whisperx[7].text 好的 我想我們可以再做進一步的說明謝謝委員長好 部長你先請回部長先請回那請國發會副主委主席不好意思 有請好 請高副主委主席長 我再請教主席長是1130我國薪水佔GDP比重是多少那還有國發會副主委你怎麼定義低薪勞工這兩個請那個主席長先回應
transcript.whisperx[8].start 185.664
transcript.whisperx[8].end 196.769
transcript.whisperx[8].text 那個我說主席長是請教你說薪水佔GDP的比重是多少這個部分薪水佔GDP的比重這個部分好像43%左右確實的數據是多少43%左右
transcript.whisperx[9].start 210.526
transcript.whisperx[9].end 229.153
transcript.whisperx[9].text 從1990年的百分之我們薪資佔GDP的比例這個部分薪資佔GDP的比例到底是多少我們現在是用受雇報酬佔GDP的部分是百分之40.3
transcript.whisperx[10].start 235.563
transcript.whisperx[10].end 243.353
transcript.whisperx[10].text 那好那妳剛剛說我國經常性薪資中位數是多少3.8萬是不是這個是在9月份的時候是3萬8啦3萬8
transcript.whisperx[11].start 245.765
transcript.whisperx[11].end 270.811
transcript.whisperx[11].text 有一些余數你沒有講啦就是37.多37274因為這是111年的113年度的那我們的部分現在到9月份平均是47000啦1到9月的平均是47000然後他的中位是38000左右那低於這個低於平均數的有多少佔了多少70%有69點多將近七成啦
transcript.whisperx[12].start 273.692
transcript.whisperx[12].end 290.346
transcript.whisperx[12].text 好 所以這個代表說勞動者所得未能隨著經濟成長同步增長對不對是不是這樣子但是我們中位數也是到38000也是到38000中位數就是表示有50以上的那個部分
transcript.whisperx[13].start 291.215
transcript.whisperx[13].end 307.176
transcript.whisperx[13].text 所以說反映出這個收入分配的不均台灣薪資成長未能有效反映出生產力的提升造成收入集中在少數的部分超過七成的壽星的這些階級它是低薪的比中位數低 對不對
transcript.whisperx[14].start 307.657
transcript.whisperx[14].end 330.725
transcript.whisperx[14].text 因為他有一部分就是說基層勞動者他的這個收入收入停滯增長停滯不是收入停滯加劇的這個貧富差距對不對其實貧富差距算跟各國比起來我們算也不是很高的部分不是很高是多高還不夠低
transcript.whisperx[15].start 333.411
transcript.whisperx[15].end 355.175
transcript.whisperx[15].text 華國啊 日本啊 還有德國啊我們用吉尼係數來看的話是0.606嘛不是 那我問你喔 那我問你主委總長主委長 3萬8是否足以支撐民眾的基本生活夠不夠 到底夠不夠3萬8是中位數啦這樣子 就看你 你的
transcript.whisperx[16].start 356.548
transcript.whisperx[16].end 380.463
transcript.whisperx[16].text 對嘛 所以就是每個這個都有不同的環境還有不同的所在地還有這些支出都不同還有現在這個通膨所以到底夠不夠那我想就是說有很大的進步空間嘛不是在這邊大家在這邊爭執我們要的是說怎麼樣來處理薪資成長跟經濟結構之間的這個矛盾問題要如何來解決嘛 對不對
transcript.whisperx[17].start 381.817
transcript.whisperx[17].end 400.503
transcript.whisperx[17].text 在衛福部方面他也有針對中低收入戶的部分有特別給予給他一些的輔助還有低薪的部分我們有保障基本工資所以這個部分還有我們也鼓勵企業加薪這些措施等等都是在提升我們整個薪資的一個水平這個好了 主席長妳請回請國發會
transcript.whisperx[18].start 409.591
transcript.whisperx[18].end 425.21
transcript.whisperx[18].text 好 副主委經濟成長模式從勞力密集走向資本化 知識化那貧富差距惡化是一個我們看到的結果所以所得從分配是指政府透過稅收還有透過社會福利支出等方式
transcript.whisperx[19].start 426.691
transcript.whisperx[19].end 454.767
transcript.whisperx[19].text 例如房屋津貼還有育兒津貼中低收入補助或長照支出但是我們台灣的這個製衡機制這個不完備以上市貴高階主管跟基層這個倍數的持續擴張來擴大比例所以目前沒有辦法避免那請問國發會針對這一類的現象有什麼具體的政策或調整這種製衡不平等的一個收入分配有什麼辦法
transcript.whisperx[20].start 456.03
transcript.whisperx[20].end 468.006
transcript.whisperx[20].text 我想這個問題可能要從多元併進的方式我們今天報告裡面也有講到除了用租稅的這些手段還有一個社福的支出的平衡以外我想產業結構的均衡發展也非常的重要
transcript.whisperx[21].start 471.371
transcript.whisperx[21].end 488.37
transcript.whisperx[21].text 然後薪資的薪資水準鼓勵企業提升薪資水準願意把經濟成長的成果分享給員工也很重要所以我們目前政府事實上是四個面向齊頭併進的方式我們希望可以達到我們剛剛委員希望達到的目標
transcript.whisperx[22].start 489.151
transcript.whisperx[22].end 511.116
transcript.whisperx[22].text 對啦 我也建議國發會就考慮加大對這些技術教育跟技能訓練這個部分然後尤其在對於中小企業的這些領域製造更多高薪的機會那希望國發會可以在更注重這方面的發展好不好好 是的 謝謝委員主席有請衛福部衛福部 呂次長
transcript.whisperx[23].start 522.351
transcript.whisperx[23].end 525.195
transcript.whisperx[23].text 委員你好次長好委員好這個衛福部好像很狀況外
transcript.whisperx[24].start 537.324
transcript.whisperx[24].end 561.47
transcript.whisperx[24].text 我們的主題是要縮短貧富差距但是衛福部還提出健保補充 保費調整要將利息 股息 租金等補充保費要增加然後把現行的每月結算改為年度計算那一年累計超過兩萬就要收取然後發現方向不對就在當日七個小時之內就匆匆忙忙的這樣子的急轉彎喊卡
transcript.whisperx[25].start 562.95
transcript.whisperx[25].end 589.228
transcript.whisperx[25].text 是因為被這個政策本身就有問題還是受到什麼樣的一個責難包委員我們現在目前都會來多方來廣正各方意見當初在構思的時候在討論的時候不是有請教了這個專家學者嗎是哪一位專家包委員因為我們這個是有關於財務方面有關健保的部分我想其實平常我們大概都會有沒有徵詢金管會當初
transcript.whisperx[26].start 591.724
transcript.whisperx[26].end 608.894
transcript.whisperx[26].text 不過委員因為這不是我負責的業務啦我負責社會福利這是兩對啦所以說儘管會作為中華民國這個掌管所有投資人相關事務的機構但是你們好像沒有詢問嘛我問過主委啦他說沒有不知道看報才知道的 對吧
transcript.whisperx[27].start 611.693
transcript.whisperx[27].end 627.083
transcript.whisperx[27].text 所以說在制定政策應該要更謹慎更嚴謹不然的話我想簽一法動全身的這樣子的一個政策你只要一條掌小資族的錢你們也要搶
transcript.whisperx[28].start 627.924
transcript.whisperx[28].end 644.655
transcript.whisperx[28].text 那導致我們很多民眾會把這些資金全部都移轉到另外的一個投資或者是國外那就連這些房價什麼的也會跟著漲對不對那簽一法動全身所以我們看到衛福部
transcript.whisperx[29].start 645.835
transcript.whisperx[29].end 664.489
transcript.whisperx[29].text 這樣子的一個草率的行為然後就當日七個小時之內就被打槍我想這部分我們不樂意我們不想再看到這樣的情況好不好 請衛福部好好檢討 謝謝非常感謝委員 謝謝謝謝顏委員接下來我們請葉元之委員