iVOD / 165517

Field Value
IVOD_ID 165517
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/165517
日期 2025-11-17
會議資料.會議代碼 委員會-11-4-26-11
會議資料.會議代碼:str 第11屆第4會期社會福利及衛生環境委員會第11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 11
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4會期社會福利及衛生環境委員會第11次全體委員會議
影片種類 Clip
開始時間 2025-11-17T11:57:58+08:00
結束時間 2025-11-17T12:06:10+08:00
影片長度 00:08:12
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/ff1e125e807f56ab362cf5b56ae215b0bfb6dfa65ed0fc1ddbd0c7f9f51010c4a26d91266f61260a5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 鄭天財Sra Kacaw
委員發言時間 11:57:58 - 12:06:10
會議時間 2025-11-17T09:00:00+08:00
會議名稱 立法院第11屆第4會期社會福利及衛生環境委員會第11次全體委員會議(事由:一、審查 (一)委員黃健豪等16人、委員陳超明等16人、委員蘇清泉等17人、委員呂玉玲等16人及委員柯志恩等16人擬具「勞工保險條例第六十三條條文修正草案」案。 (二)委員陳瑩等19人擬具「勞工保險條例第五十八條條文修正草案」案。 (三)委員許宇甄等19人、委員林國成等32人、委員王育敏等20人、委員蔡其昌等19人、委員羅廷瑋等16人、委員蔡易餘等18人、委員王美惠等17人、委員徐欣瑩等22人、委員翁曉玲等19人、委員楊曜等25人及委員王鴻薇等22人擬具「勞工保險條例第六十六條及第六十九條條文修正草案」案。 (四)委員邱鎮軍等19人擬具「勞工保險條例第三十一條條文修正草案」案。 (五)委員李昆澤等25人及委員賴瑞隆等17人擬具「勞工保險條例第六十九條條文修正草案」案。 (六)委員廖先翔等18人擬具「勞工保險條例第十九條條文修正草案」案。 (七)委員葉元之等21人、委員何欣純等17人及委員陳超明等16人擬具「勞工保險條例第五十八條條文修正草案」案。 (八)委員陳秀寳等21人擬具「勞工保險條例部分條文修正草案」案。 (九)委員王鴻薇等17人擬具「勞工保險條例第七十四條之二條文修正草案」案。 (十)委員林倩綺等32人及委員傅崐萁等19人擬具「勞工保險條例第五十九條條文修正草案」案。 (十一)委員陳瑩等19人擬具「勞工保險條例第六條條文修正草案」案。 (十二)委員李昆澤等19人擬具「勞工保險條例第二十九條條文修正草案」案。 二、審查 (一)委員陳玉珍等18人擬具「就業服務法第二十四條及第二十七條條文修正草案」案。 (二)委員涂權吉等17人擬具「就業服務法第二十四條條文修正草案」案。 (三)委員許宇甄等18人擬具「就業服務法第二十四條條文修正草案」案。 (四)委員翁曉玲等22人擬具「就業服務法第二十四條條文修正草案」案。 (五)委員蘇清泉等18人擬具「就業服務法第二十四條條文修正草案」案。 (六)委員廖偉翔等16人擬具「就業服務法第二十四條條文修正草案」案。 (七)委員洪孟楷等16人擬具「就業服務法第二十四條條文修正草案」案。 (八)台灣民眾黨黨團擬具「就業服務法第二十四條條文修正草案」案。 (九)委員柯志恩等18人擬具「就業服務法第二十四條條文修正草案」案。 (十)委員王育敏等17人擬具「就業服務法第二十四條、第二十七條及第二十八條條文修正草案」案。 (十一)委員楊瓊瓔等27人擬具「就業服務法第二十四條條文修正草案」案。 (十二)委員郭國文等19人擬具「就業服務法第二十四條及第二十六條之一條文修正草案」案。 【綜合詢答,僅詢答】)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 17.51346875
transcript.pyannote[0].end 19.85909375
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 21.98534375
transcript.pyannote[1].end 22.13721875
transcript.pyannote[2].speaker SPEAKER_03
transcript.pyannote[2].start 22.13721875
transcript.pyannote[2].end 22.15409375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 22.15409375
transcript.pyannote[3].end 22.17096875
transcript.pyannote[4].speaker SPEAKER_03
transcript.pyannote[4].start 22.17096875
transcript.pyannote[4].end 22.69409375
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 22.69409375
transcript.pyannote[5].end 22.77846875
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 23.90909375
transcript.pyannote[6].end 27.04784375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 32.65034375
transcript.pyannote[7].end 32.66721875
transcript.pyannote[8].speaker SPEAKER_03
transcript.pyannote[8].start 32.66721875
transcript.pyannote[8].end 33.59534375
transcript.pyannote[9].speaker SPEAKER_03
transcript.pyannote[9].start 33.96659375
transcript.pyannote[9].end 34.03409375
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 34.03409375
transcript.pyannote[10].end 34.28721875
transcript.pyannote[11].speaker SPEAKER_03
transcript.pyannote[11].start 34.28721875
transcript.pyannote[11].end 38.67471875
transcript.pyannote[12].speaker SPEAKER_03
transcript.pyannote[12].start 39.16409375
transcript.pyannote[12].end 42.99471875
transcript.pyannote[13].speaker SPEAKER_03
transcript.pyannote[13].start 43.58534375
transcript.pyannote[13].end 50.48721875
transcript.pyannote[14].speaker SPEAKER_03
transcript.pyannote[14].start 50.65596875
transcript.pyannote[14].end 53.13659375
transcript.pyannote[15].speaker SPEAKER_03
transcript.pyannote[15].start 53.79471875
transcript.pyannote[15].end 56.24159375
transcript.pyannote[16].speaker SPEAKER_03
transcript.pyannote[16].start 57.84471875
transcript.pyannote[16].end 59.16096875
transcript.pyannote[17].speaker SPEAKER_03
transcript.pyannote[17].start 59.56596875
transcript.pyannote[17].end 60.76409375
transcript.pyannote[18].speaker SPEAKER_03
transcript.pyannote[18].start 61.52346875
transcript.pyannote[18].end 66.40034375
transcript.pyannote[19].speaker SPEAKER_03
transcript.pyannote[19].start 67.27784375
transcript.pyannote[19].end 70.24784375
transcript.pyannote[20].speaker SPEAKER_03
transcript.pyannote[20].start 70.75409375
transcript.pyannote[20].end 72.74534375
transcript.pyannote[21].speaker SPEAKER_03
transcript.pyannote[21].start 73.48784375
transcript.pyannote[21].end 77.90909375
transcript.pyannote[22].speaker SPEAKER_03
transcript.pyannote[22].start 78.83721875
transcript.pyannote[22].end 79.95096875
transcript.pyannote[23].speaker SPEAKER_03
transcript.pyannote[23].start 80.42346875
transcript.pyannote[23].end 80.89596875
transcript.pyannote[24].speaker SPEAKER_03
transcript.pyannote[24].start 81.68909375
transcript.pyannote[24].end 83.15721875
transcript.pyannote[25].speaker SPEAKER_03
transcript.pyannote[25].start 83.81534375
transcript.pyannote[25].end 84.10221875
transcript.pyannote[26].speaker SPEAKER_03
transcript.pyannote[26].start 84.59159375
transcript.pyannote[26].end 85.23284375
transcript.pyannote[27].speaker SPEAKER_03
transcript.pyannote[27].start 85.63784375
transcript.pyannote[27].end 87.12284375
transcript.pyannote[28].speaker SPEAKER_03
transcript.pyannote[28].start 88.01721875
transcript.pyannote[28].end 88.33784375
transcript.pyannote[29].speaker SPEAKER_03
transcript.pyannote[29].start 88.48971875
transcript.pyannote[29].end 90.32909375
transcript.pyannote[30].speaker SPEAKER_03
transcript.pyannote[30].start 90.76784375
transcript.pyannote[30].end 92.13471875
transcript.pyannote[31].speaker SPEAKER_03
transcript.pyannote[31].start 92.18534375
transcript.pyannote[31].end 93.43409375
transcript.pyannote[32].speaker SPEAKER_03
transcript.pyannote[32].start 94.37909375
transcript.pyannote[32].end 96.43784375
transcript.pyannote[33].speaker SPEAKER_03
transcript.pyannote[33].start 98.69909375
transcript.pyannote[33].end 99.13784375
transcript.pyannote[34].speaker SPEAKER_03
transcript.pyannote[34].start 99.88034375
transcript.pyannote[34].end 100.52159375
transcript.pyannote[35].speaker SPEAKER_03
transcript.pyannote[35].start 101.17971875
transcript.pyannote[35].end 103.59284375
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 104.52096875
transcript.pyannote[36].end 107.84534375
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 108.30096875
transcript.pyannote[37].end 109.44846875
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 109.81971875
transcript.pyannote[38].end 112.40159375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 113.04284375
transcript.pyannote[39].end 114.84846875
transcript.pyannote[40].speaker SPEAKER_03
transcript.pyannote[40].start 115.87784375
transcript.pyannote[40].end 117.71721875
transcript.pyannote[41].speaker SPEAKER_03
transcript.pyannote[41].start 118.47659375
transcript.pyannote[41].end 119.35409375
transcript.pyannote[42].speaker SPEAKER_03
transcript.pyannote[42].start 119.62409375
transcript.pyannote[42].end 124.24784375
transcript.pyannote[43].speaker SPEAKER_03
transcript.pyannote[43].start 125.46284375
transcript.pyannote[43].end 126.34034375
transcript.pyannote[44].speaker SPEAKER_03
transcript.pyannote[44].start 127.72409375
transcript.pyannote[44].end 130.81221875
transcript.pyannote[45].speaker SPEAKER_03
transcript.pyannote[45].start 131.94284375
transcript.pyannote[45].end 132.93846875
transcript.pyannote[46].speaker SPEAKER_03
transcript.pyannote[46].start 133.52909375
transcript.pyannote[46].end 136.21221875
transcript.pyannote[47].speaker SPEAKER_03
transcript.pyannote[47].start 136.75221875
transcript.pyannote[47].end 138.01784375
transcript.pyannote[48].speaker SPEAKER_03
transcript.pyannote[48].start 138.49034375
transcript.pyannote[48].end 140.98784375
transcript.pyannote[49].speaker SPEAKER_03
transcript.pyannote[49].start 141.73034375
transcript.pyannote[49].end 143.99159375
transcript.pyannote[50].speaker SPEAKER_03
transcript.pyannote[50].start 144.56534375
transcript.pyannote[50].end 148.09221875
transcript.pyannote[51].speaker SPEAKER_03
transcript.pyannote[51].start 148.73346875
transcript.pyannote[51].end 150.79221875
transcript.pyannote[52].speaker SPEAKER_03
transcript.pyannote[52].start 150.89346875
transcript.pyannote[52].end 151.72034375
transcript.pyannote[53].speaker SPEAKER_03
transcript.pyannote[53].start 152.59784375
transcript.pyannote[53].end 154.06596875
transcript.pyannote[54].speaker SPEAKER_03
transcript.pyannote[54].start 154.89284375
transcript.pyannote[54].end 155.17971875
transcript.pyannote[55].speaker SPEAKER_03
transcript.pyannote[55].start 155.97284375
transcript.pyannote[55].end 157.66034375
transcript.pyannote[56].speaker SPEAKER_03
transcript.pyannote[56].start 157.99784375
transcript.pyannote[56].end 164.88284375
transcript.pyannote[57].speaker SPEAKER_03
transcript.pyannote[57].start 166.90784375
transcript.pyannote[57].end 167.31284375
transcript.pyannote[58].speaker SPEAKER_03
transcript.pyannote[58].start 168.12284375
transcript.pyannote[58].end 170.65409375
transcript.pyannote[59].speaker SPEAKER_03
transcript.pyannote[59].start 171.46409375
transcript.pyannote[59].end 173.05034375
transcript.pyannote[60].speaker SPEAKER_03
transcript.pyannote[60].start 173.91096875
transcript.pyannote[60].end 175.27784375
transcript.pyannote[61].speaker SPEAKER_03
transcript.pyannote[61].start 175.78409375
transcript.pyannote[61].end 177.62346875
transcript.pyannote[62].speaker SPEAKER_03
transcript.pyannote[62].start 178.97346875
transcript.pyannote[62].end 179.54721875
transcript.pyannote[63].speaker SPEAKER_03
transcript.pyannote[63].start 180.22221875
transcript.pyannote[63].end 187.02284375
transcript.pyannote[64].speaker SPEAKER_03
transcript.pyannote[64].start 187.20846875
transcript.pyannote[64].end 189.14909375
transcript.pyannote[65].speaker SPEAKER_03
transcript.pyannote[65].start 189.58784375
transcript.pyannote[65].end 191.96721875
transcript.pyannote[66].speaker SPEAKER_03
transcript.pyannote[66].start 192.65909375
transcript.pyannote[66].end 193.18221875
transcript.pyannote[67].speaker SPEAKER_03
transcript.pyannote[67].start 193.72221875
transcript.pyannote[67].end 197.55284375
transcript.pyannote[68].speaker SPEAKER_03
transcript.pyannote[68].start 198.12659375
transcript.pyannote[68].end 198.88596875
transcript.pyannote[69].speaker SPEAKER_03
transcript.pyannote[69].start 199.61159375
transcript.pyannote[69].end 201.46784375
transcript.pyannote[70].speaker SPEAKER_03
transcript.pyannote[70].start 202.26096875
transcript.pyannote[70].end 203.42534375
transcript.pyannote[71].speaker SPEAKER_03
transcript.pyannote[71].start 203.86409375
transcript.pyannote[71].end 204.75846875
transcript.pyannote[72].speaker SPEAKER_03
transcript.pyannote[72].start 204.96096875
transcript.pyannote[72].end 207.34034375
transcript.pyannote[73].speaker SPEAKER_03
transcript.pyannote[73].start 207.79596875
transcript.pyannote[73].end 209.04471875
transcript.pyannote[74].speaker SPEAKER_03
transcript.pyannote[74].start 209.17971875
transcript.pyannote[74].end 211.81221875
transcript.pyannote[75].speaker SPEAKER_03
transcript.pyannote[75].start 212.47034375
transcript.pyannote[75].end 214.88346875
transcript.pyannote[76].speaker SPEAKER_03
transcript.pyannote[76].start 215.77784375
transcript.pyannote[76].end 217.60034375
transcript.pyannote[77].speaker SPEAKER_03
transcript.pyannote[77].start 218.54534375
transcript.pyannote[77].end 219.38909375
transcript.pyannote[78].speaker SPEAKER_03
transcript.pyannote[78].start 219.76034375
transcript.pyannote[78].end 221.61659375
transcript.pyannote[79].speaker SPEAKER_03
transcript.pyannote[79].start 222.20721875
transcript.pyannote[79].end 222.76409375
transcript.pyannote[80].speaker SPEAKER_03
transcript.pyannote[80].start 223.62471875
transcript.pyannote[80].end 224.51909375
transcript.pyannote[81].speaker SPEAKER_03
transcript.pyannote[81].start 225.98721875
transcript.pyannote[81].end 227.94471875
transcript.pyannote[82].speaker SPEAKER_03
transcript.pyannote[82].start 228.70409375
transcript.pyannote[82].end 230.22284375
transcript.pyannote[83].speaker SPEAKER_03
transcript.pyannote[83].start 230.88096875
transcript.pyannote[83].end 232.46721875
transcript.pyannote[84].speaker SPEAKER_03
transcript.pyannote[84].start 233.90159375
transcript.pyannote[84].end 236.02784375
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 236.02784375
transcript.pyannote[85].end 236.38221875
transcript.pyannote[86].speaker SPEAKER_03
transcript.pyannote[86].start 236.38221875
transcript.pyannote[86].end 236.65221875
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 237.86721875
transcript.pyannote[87].end 254.08409375
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 254.79284375
transcript.pyannote[88].end 255.51846875
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 255.85596875
transcript.pyannote[89].end 260.49659375
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 260.93534375
transcript.pyannote[90].end 274.68846875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 275.11034375
transcript.pyannote[91].end 281.08409375
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 281.42159375
transcript.pyannote[92].end 299.71409375
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 299.98409375
transcript.pyannote[93].end 302.19471875
transcript.pyannote[94].speaker SPEAKER_03
transcript.pyannote[94].start 303.00471875
transcript.pyannote[94].end 305.16471875
transcript.pyannote[95].speaker SPEAKER_03
transcript.pyannote[95].start 306.49784375
transcript.pyannote[95].end 310.02471875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 310.02471875
transcript.pyannote[96].end 310.14284375
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 310.80096875
transcript.pyannote[97].end 342.23909375
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 326.14034375
transcript.pyannote[98].end 326.24159375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 343.04909375
transcript.pyannote[99].end 343.11659375
transcript.pyannote[100].speaker SPEAKER_03
transcript.pyannote[100].start 343.11659375
transcript.pyannote[100].end 347.04846875
transcript.pyannote[101].speaker SPEAKER_03
transcript.pyannote[101].start 347.84159375
transcript.pyannote[101].end 349.78221875
transcript.pyannote[102].speaker SPEAKER_03
transcript.pyannote[102].start 351.43596875
transcript.pyannote[102].end 353.61284375
transcript.pyannote[103].speaker SPEAKER_03
transcript.pyannote[103].start 354.30471875
transcript.pyannote[103].end 360.21096875
transcript.pyannote[104].speaker SPEAKER_03
transcript.pyannote[104].start 360.37971875
transcript.pyannote[104].end 361.72971875
transcript.pyannote[105].speaker SPEAKER_03
transcript.pyannote[105].start 362.52284375
transcript.pyannote[105].end 363.95721875
transcript.pyannote[106].speaker SPEAKER_03
transcript.pyannote[106].start 364.54784375
transcript.pyannote[106].end 366.62346875
transcript.pyannote[107].speaker SPEAKER_03
transcript.pyannote[107].start 367.68659375
transcript.pyannote[107].end 370.55534375
transcript.pyannote[108].speaker SPEAKER_03
transcript.pyannote[108].start 370.82534375
transcript.pyannote[108].end 372.19221875
transcript.pyannote[109].speaker SPEAKER_03
transcript.pyannote[109].start 372.69846875
transcript.pyannote[109].end 376.57971875
transcript.pyannote[110].speaker SPEAKER_01
transcript.pyannote[110].start 376.57971875
transcript.pyannote[110].end 376.61346875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 376.71471875
transcript.pyannote[111].end 382.89096875
transcript.pyannote[112].speaker SPEAKER_01
transcript.pyannote[112].start 383.97096875
transcript.pyannote[112].end 390.55221875
transcript.pyannote[113].speaker SPEAKER_03
transcript.pyannote[113].start 390.55221875
transcript.pyannote[113].end 392.37471875
transcript.pyannote[114].speaker SPEAKER_03
transcript.pyannote[114].start 393.26909375
transcript.pyannote[114].end 394.12971875
transcript.pyannote[115].speaker SPEAKER_03
transcript.pyannote[115].start 394.28159375
transcript.pyannote[115].end 401.48721875
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 401.84159375
transcript.pyannote[116].end 419.96534375
transcript.pyannote[117].speaker SPEAKER_03
transcript.pyannote[117].start 417.23159375
transcript.pyannote[117].end 418.34534375
transcript.pyannote[118].speaker SPEAKER_03
transcript.pyannote[118].start 418.83471875
transcript.pyannote[118].end 425.90534375
transcript.pyannote[119].speaker SPEAKER_03
transcript.pyannote[119].start 426.59721875
transcript.pyannote[119].end 431.38971875
transcript.pyannote[120].speaker SPEAKER_03
transcript.pyannote[120].start 431.98034375
transcript.pyannote[120].end 435.15284375
transcript.pyannote[121].speaker SPEAKER_03
transcript.pyannote[121].start 435.54096875
transcript.pyannote[121].end 439.28721875
transcript.pyannote[122].speaker SPEAKER_03
transcript.pyannote[122].start 439.75971875
transcript.pyannote[122].end 440.58659375
transcript.pyannote[123].speaker SPEAKER_03
transcript.pyannote[123].start 441.05909375
transcript.pyannote[123].end 442.15596875
transcript.pyannote[124].speaker SPEAKER_03
transcript.pyannote[124].start 442.62846875
transcript.pyannote[124].end 445.39596875
transcript.pyannote[125].speaker SPEAKER_03
transcript.pyannote[125].start 445.91909375
transcript.pyannote[125].end 448.06221875
transcript.pyannote[126].speaker SPEAKER_03
transcript.pyannote[126].start 448.85534375
transcript.pyannote[126].end 449.54721875
transcript.pyannote[127].speaker SPEAKER_03
transcript.pyannote[127].start 450.99846875
transcript.pyannote[127].end 454.20471875
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 454.52534375
transcript.pyannote[128].end 457.47846875
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 457.81596875
transcript.pyannote[129].end 460.85346875
transcript.pyannote[130].speaker SPEAKER_03
transcript.pyannote[130].start 460.36409375
transcript.pyannote[130].end 463.55346875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 463.55346875
transcript.pyannote[131].end 464.88659375
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 465.00471875
transcript.pyannote[132].end 467.19846875
transcript.pyannote[133].speaker SPEAKER_03
transcript.pyannote[133].start 465.27471875
transcript.pyannote[133].end 470.42159375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 469.98284375
transcript.pyannote[134].end 473.67846875
transcript.pyannote[135].speaker SPEAKER_03
transcript.pyannote[135].start 472.12596875
transcript.pyannote[135].end 479.41596875
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 475.36596875
transcript.pyannote[136].end 478.21784375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 479.16284375
transcript.pyannote[137].end 481.05284375
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 482.47034375
transcript.pyannote[138].end 485.59221875
transcript.pyannote[139].speaker SPEAKER_03
transcript.pyannote[139].start 485.91284375
transcript.pyannote[139].end 489.74346875
transcript.whisperx[0].start 24.142
transcript.whisperx[0].end 42.696
transcript.whisperx[0].text 主席 請部長部長好這個原住民與非原住民的平均移民的落差一直都非常大
transcript.whisperx[1].start 44.169
transcript.whisperx[1].end 66.154
transcript.whisperx[1].text 我們就以去年來講 平均落差是7.54這個年齡如果我們從山地原住民 平均落差是9歲如果是男生 就男生而言 山地原住民是10.38歲的落差 平均移民
transcript.whisperx[2].start 67.752
transcript.whisperx[2].end 95.212
transcript.whisperx[2].text 整體原住民是8.77這個平均裡面的落差在這樣一個情形之下所以我們相關的這些無論是這個公教警消軍人或是尤其是勞工這相關的這些潛意就會受到很大的落差的影響
transcript.whisperx[3].start 98.775
transcript.whisperx[3].end 126.11
transcript.whisperx[3].text 所以过去啊我们就政府机关都会重视唯独现在一直还没有完成的就是我们的劳工的部分我们看国民年金法第53条国民年金法定了很久了年满55岁的原住民一般非原住民是65岁原住民就是55岁我们看这个
transcript.whisperx[4].start 127.759
transcript.whisperx[4].end 153.827
transcript.whisperx[4].text 公务人员退休之前府系法也特别明定一般的公务人员是60岁就自愿退休原住民降为55岁就是有他的实际的年龄平均移民实际的落差的关系公立学校的教职员也是一样法律都这样定的
transcript.whisperx[5].start 156.024
transcript.whisperx[5].end 177.41
transcript.whisperx[5].text 原住民在教職員公立學校教職員也是原住民身份者降為55歲就比一般的退休年齡可以降連農民退休儲金這是新的法例農民退休儲金條例本席在審查委員會提案的時候針對
transcript.whisperx[6].start 180.287
transcript.whisperx[6].end 201.304
transcript.whisperx[6].text 原住民的部分全国原住民跟身心障碍要不同的所以法律就明定要按照他的平均移民来去计算所以农民退休除菌条例的施行细则根据这个条例然后定了施行细则
transcript.whisperx[7].start 202.321
transcript.whisperx[7].end 227.743
transcript.whisperx[7].text 也是要去七分全國原住民身心障礙的生命移民移民來去訂定所以這個都是有一個已經有法律的依據了法律的可以參考所以這個部長所以我們原住民的部分
transcript.whisperx[8].start 228.789
transcript.whisperx[8].end 253.206
transcript.whisperx[8].text 在勞工的部分是不是也應該要比照來訂定請我們市長來跟委員報告 剛我有提到那個國民年金的那個是原住民給付原住民給付那是一個津貼的性質是由原民會編列公務預算來發的那國保的老年年金也是原住民的部分也是跟平常人一樣都是在65歲
transcript.whisperx[9].start 254.867
transcript.whisperx[9].end 273.349
transcript.whisperx[9].text 發給那在勞工的這個部分主要是因為原住民整個勞工經濟整體的保障我們覺得不只是保險包括就業促進跟社會津貼的這個部分那嚴明也跟我們一樣都是
transcript.whisperx[10].start 275.191
transcript.whisperx[10].end 301.844
transcript.whisperx[10].text 慢慢人口在高齡化所以整個社會保險都是採 逐步提高青年年齡的機制那老保的部分我們已經有可以提前五年齡減而年輕的機制那整個老年幾戶也不是用平均餘命來當基礎所以為了制度的公平跟財務的安定整個幾戶條件應該跟一般的人一樣因為我沒有分族群那以上跟各位跟委員報告
transcript.whisperx[11].start 303.055
transcript.whisperx[11].end 320.293
transcript.whisperx[11].text 那個部長你支持剛才的同仁的說明嗎跟這位說明當然市長其實在講的確實是在整體政策上面的一些思考的點那其實從
transcript.whisperx[12].start 323.016
transcript.whisperx[12].end 349.213
transcript.whisperx[12].text 從保險司或者是從我們在思考整體勞保年金的改革的勞保年金整體的制度來說的確會一直要去顧及一個相關的橫平性那尤其是一個比較完整機制的部分所以確實在這個基金的運作裡面比較沒有從身分別那去做差別化的處理剛才你那一計畫部長那一計畫橫平性很重要就是要從橫平性
transcript.whisperx[13].start 351.479
transcript.whisperx[13].end 366.321
transcript.whisperx[13].text 刚才的说明都没有横平性就是因为要横平所以要按照实际的情形我们就讲年龄他就有这么大的平均移民的落差
transcript.whisperx[14].start 367.711
transcript.whisperx[14].end 391.053
transcript.whisperx[14].text 就不橫貧嗎 按照現在的法律就不橫貧嗎按照你勞動部所主管的這些法律就不橫貧嗎跟我們說 因為現在比較會有的討論比較是在青年年齡是不是要往更高來去拉所以對於要把某些部分的青年年齡要再往下降這件事情確實是需要比較多的考慮所以你對這個
transcript.whisperx[15].start 393.625
transcript.whisperx[15].end 418.802
transcript.whisperx[15].text 原住民跟非原住民的平均移民有這麼大的落差毫無手感所以這個部分跟委員不是這樣子的比方說我們就我們在這個平均移民的問題上我在當委員的時候我們也很支持比方說透過原建法或等等等等盡量的來讓我們在原住民族的這個健康的狀態或者是這個那個部長大家能夠來努力那個已經
transcript.whisperx[16].start 420.723
transcript.whisperx[16].end 449.375
transcript.whisperx[16].text 你那樣的說法已經最起碼10年以上都是這樣的說法啦而事實上我剛特別擠了這麼多的法例從國民年金法降為55歲公立學校教職員降為55歲我們的公務人員的法例也是降為55歲農民退休儲金的條例
transcript.whisperx[17].start 451.038
transcript.whisperx[17].end 453.977
transcript.whisperx[17].text 这是最新的法力这是上一届才完成的
transcript.whisperx[18].start 454.591
transcript.whisperx[18].end 479.643
transcript.whisperx[18].text 我應該說的部分都是退休金的部分不是這個一樣的他不是社會保險跟勞工保險不是一樣還是看年齡跟文說明老保是你沒有年齡嗎還有年齡的規定跟文說明老保是我們在主條審查的時候再好好討論老保是社會保險然後剛剛的退休金的部分有他在這個
transcript.whisperx[19].start 482.586
transcript.whisperx[19].end 488.344
transcript.whisperx[19].text 上面退休性質跟社會保險還是有不同的好我們在主條的時候再好好討論好謝謝