iVOD / 159976

Field Value
IVOD_ID 159976
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/159976
日期 2025-04-09
會議資料.會議代碼 委員會-11-3-26-5
會議資料.會議代碼:str 第11屆第3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 3
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3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 2025-04-09T11:34:07+08:00
結束時間 2025-04-09T11:48:42+08:00
影片長度 00:14:35
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/984603a5a250cdce0717e0adb842796ba9dd72f8e909e2232eb6e21b32d8c6be6c7b4370730bc6965ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 蘇清泉
委員發言時間 11:34:07 - 11:48:42
會議時間 2025-04-09T09:00:00+08:00
會議名稱 立法院第11屆第3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:邀請勞動部部長對於「勞動部所屬基金違規使用如何追回及究責」進行專題報告,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_03
transcript.pyannote[0].start 2.96721875
transcript.pyannote[0].end 5.24534375
transcript.pyannote[1].speaker SPEAKER_03
transcript.pyannote[1].start 7.45596875
transcript.pyannote[1].end 8.02971875
transcript.pyannote[2].speaker SPEAKER_03
transcript.pyannote[2].start 8.29971875
transcript.pyannote[2].end 8.33346875
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 8.33346875
transcript.pyannote[3].end 8.62034375
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 11.80971875
transcript.pyannote[4].end 15.11721875
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 16.56846875
transcript.pyannote[5].end 19.04909375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 29.66346875
transcript.pyannote[6].end 29.68034375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 29.68034375
transcript.pyannote[7].end 29.96721875
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 29.96721875
transcript.pyannote[8].end 31.16534375
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 30.15284375
transcript.pyannote[9].end 30.45659375
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 30.45659375
transcript.pyannote[10].end 30.67596875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 30.81096875
transcript.pyannote[11].end 31.03034375
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 31.16534375
transcript.pyannote[12].end 31.73909375
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 32.32971875
transcript.pyannote[13].end 33.03846875
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 33.96659375
transcript.pyannote[14].end 36.32909375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 36.53159375
transcript.pyannote[15].end 36.73409375
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 36.73409375
transcript.pyannote[16].end 45.84659375
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 46.25159375
transcript.pyannote[17].end 56.62971875
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 57.57471875
transcript.pyannote[18].end 77.03159375
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 77.40284375
transcript.pyannote[19].end 80.62596875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 80.92971875
transcript.pyannote[20].end 82.11096875
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 82.49909375
transcript.pyannote[21].end 93.65346875
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 93.48471875
transcript.pyannote[22].end 105.33096875
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 106.05659375
transcript.pyannote[23].end 109.81971875
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 110.03909375
transcript.pyannote[24].end 116.45159375
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 116.78909375
transcript.pyannote[25].end 122.25659375
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 122.59409375
transcript.pyannote[26].end 127.01534375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 127.89284375
transcript.pyannote[27].end 138.81096875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 139.62096875
transcript.pyannote[28].end 141.35909375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 141.54471875
transcript.pyannote[29].end 166.46909375
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 166.84034375
transcript.pyannote[30].end 168.74721875
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 169.54034375
transcript.pyannote[31].end 176.37471875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 176.54346875
transcript.pyannote[32].end 181.94346875
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 182.19659375
transcript.pyannote[33].end 186.02721875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 186.14534375
transcript.pyannote[34].end 192.32159375
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 192.11909375
transcript.pyannote[35].end 196.77659375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 198.43034375
transcript.pyannote[36].end 199.96596875
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 199.96596875
transcript.pyannote[37].end 204.82596875
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 205.26471875
transcript.pyannote[38].end 205.70346875
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 206.36159375
transcript.pyannote[39].end 210.39471875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 211.01909375
transcript.pyannote[40].end 217.29659375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 217.49909375
transcript.pyannote[41].end 227.57346875
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 228.07971875
transcript.pyannote[42].end 231.15096875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 232.41659375
transcript.pyannote[43].end 234.25596875
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 232.58534375
transcript.pyannote[44].end 234.42471875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 234.39096875
transcript.pyannote[45].end 236.65221875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 237.88409375
transcript.pyannote[46].end 238.64346875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 239.80784375
transcript.pyannote[47].end 243.21659375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 242.35596875
transcript.pyannote[48].end 243.97596875
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 243.67221875
transcript.pyannote[49].end 253.27409375
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 254.91096875
transcript.pyannote[50].end 255.88971875
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 254.94471875
transcript.pyannote[51].end 255.40034375
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 256.00784375
transcript.pyannote[52].end 264.91784375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 264.78284375
transcript.pyannote[53].end 265.96409375
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 266.40284375
transcript.pyannote[54].end 267.87096875
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 268.56284375
transcript.pyannote[55].end 271.17846875
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 271.17846875
transcript.pyannote[56].end 272.15721875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 272.91659375
transcript.pyannote[57].end 273.57471875
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 274.28346875
transcript.pyannote[58].end 276.08909375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 276.44346875
transcript.pyannote[59].end 278.89034375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 279.16034375
transcript.pyannote[60].end 282.94034375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 283.69971875
transcript.pyannote[61].end 286.85534375
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 287.05784375
transcript.pyannote[62].end 289.47096875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 289.97721875
transcript.pyannote[63].end 299.32596875
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 299.73096875
transcript.pyannote[64].end 316.47096875
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 316.60596875
transcript.pyannote[65].end 330.05534375
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 326.76471875
transcript.pyannote[66].end 326.81534375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 330.84846875
transcript.pyannote[67].end 340.02846875
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 334.66221875
transcript.pyannote[68].end 334.67909375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 334.67909375
transcript.pyannote[69].end 334.72971875
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 334.72971875
transcript.pyannote[70].end 334.78034375
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 334.78034375
transcript.pyannote[71].end 334.83096875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 334.83096875
transcript.pyannote[72].end 334.96596875
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 335.59034375
transcript.pyannote[73].end 335.62409375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 339.06659375
transcript.pyannote[74].end 339.08346875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 340.02846875
transcript.pyannote[75].end 358.01721875
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 340.50096875
transcript.pyannote[76].end 340.90596875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 358.32096875
transcript.pyannote[77].end 358.62471875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 358.62471875
transcript.pyannote[78].end 358.67534375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 358.67534375
transcript.pyannote[79].end 358.69221875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 358.84409375
transcript.pyannote[80].end 362.48909375
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 361.45971875
transcript.pyannote[81].end 365.54346875
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 366.21846875
transcript.pyannote[82].end 367.99034375
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 368.61471875
transcript.pyannote[83].end 368.63159375
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 368.63159375
transcript.pyannote[84].end 369.84659375
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 370.33596875
transcript.pyannote[85].end 370.97721875
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 371.09534375
transcript.pyannote[86].end 372.17534375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 372.44534375
transcript.pyannote[87].end 374.58846875
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 374.58846875
transcript.pyannote[88].end 382.80659375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 383.02596875
transcript.pyannote[89].end 406.83659375
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 407.52846875
transcript.pyannote[90].end 409.78971875
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 410.21159375
transcript.pyannote[91].end 411.24096875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 421.12971875
transcript.pyannote[92].end 425.23034375
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 425.93909375
transcript.pyannote[93].end 431.76096875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 432.36846875
transcript.pyannote[94].end 434.05596875
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 434.79846875
transcript.pyannote[95].end 438.03846875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 438.25784375
transcript.pyannote[96].end 438.67971875
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 439.60784375
transcript.pyannote[97].end 440.24909375
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 440.63721875
transcript.pyannote[98].end 449.59784375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 450.52596875
transcript.pyannote[99].end 454.20471875
transcript.pyannote[100].speaker SPEAKER_03
transcript.pyannote[100].start 459.60471875
transcript.pyannote[100].end 462.49034375
transcript.pyannote[101].speaker SPEAKER_03
transcript.pyannote[101].start 463.30034375
transcript.pyannote[101].end 463.33409375
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 463.33409375
transcript.pyannote[102].end 475.45034375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 475.66971875
transcript.pyannote[103].end 479.14596875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 479.53409375
transcript.pyannote[104].end 488.37659375
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 488.73096875
transcript.pyannote[105].end 490.94159375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 491.85284375
transcript.pyannote[106].end 498.24846875
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 498.63659375
transcript.pyannote[107].end 508.23846875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 508.39034375
transcript.pyannote[108].end 508.40721875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 508.49159375
transcript.pyannote[109].end 516.03471875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 516.16971875
transcript.pyannote[110].end 519.64596875
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 521.63721875
transcript.pyannote[111].end 532.58909375
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 533.26409375
transcript.pyannote[112].end 535.44096875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 536.43659375
transcript.pyannote[113].end 543.13596875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 544.11471875
transcript.pyannote[114].end 563.04846875
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 563.95971875
transcript.pyannote[115].end 569.41034375
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 570.10221875
transcript.pyannote[116].end 570.79409375
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 571.40159375
transcript.pyannote[117].end 571.87409375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 572.90346875
transcript.pyannote[118].end 580.02471875
transcript.pyannote[119].speaker SPEAKER_03
transcript.pyannote[119].start 580.02471875
transcript.pyannote[119].end 580.93596875
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 580.93596875
transcript.pyannote[120].end 580.96971875
transcript.pyannote[121].speaker SPEAKER_03
transcript.pyannote[121].start 580.96971875
transcript.pyannote[121].end 580.98659375
transcript.pyannote[122].speaker SPEAKER_03
transcript.pyannote[122].start 581.44221875
transcript.pyannote[122].end 623.79846875
transcript.pyannote[123].speaker SPEAKER_03
transcript.pyannote[123].start 624.89534375
transcript.pyannote[123].end 633.65346875
transcript.pyannote[124].speaker SPEAKER_03
transcript.pyannote[124].start 634.22721875
transcript.pyannote[124].end 636.60659375
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 635.52659375
transcript.pyannote[125].end 639.00284375
transcript.pyannote[126].speaker SPEAKER_03
transcript.pyannote[126].start 639.00284375
transcript.pyannote[126].end 639.72846875
transcript.pyannote[127].speaker SPEAKER_03
transcript.pyannote[127].start 639.99846875
transcript.pyannote[127].end 688.66596875
transcript.pyannote[128].speaker SPEAKER_02
transcript.pyannote[128].start 688.66596875
transcript.pyannote[128].end 688.76721875
transcript.pyannote[129].speaker SPEAKER_03
transcript.pyannote[129].start 688.76721875
transcript.pyannote[129].end 688.96971875
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 688.96971875
transcript.pyannote[130].end 697.33971875
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 697.96409375
transcript.pyannote[131].end 699.36471875
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 699.83721875
transcript.pyannote[132].end 704.05596875
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 704.96721875
transcript.pyannote[133].end 729.08159375
transcript.pyannote[134].speaker SPEAKER_03
transcript.pyannote[134].start 728.87909375
transcript.pyannote[134].end 729.06471875
transcript.pyannote[135].speaker SPEAKER_03
transcript.pyannote[135].start 729.08159375
transcript.pyannote[135].end 731.98409375
transcript.pyannote[136].speaker SPEAKER_03
transcript.pyannote[136].start 732.45659375
transcript.pyannote[136].end 738.39659375
transcript.pyannote[137].speaker SPEAKER_03
transcript.pyannote[137].start 739.24034375
transcript.pyannote[137].end 740.97846875
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 740.97846875
transcript.pyannote[138].end 750.02346875
transcript.pyannote[139].speaker SPEAKER_03
transcript.pyannote[139].start 750.02346875
transcript.pyannote[139].end 750.79971875
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 750.79971875
transcript.pyannote[140].end 750.83346875
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 751.89659375
transcript.pyannote[141].end 751.91346875
transcript.pyannote[142].speaker SPEAKER_03
transcript.pyannote[142].start 751.91346875
transcript.pyannote[142].end 753.93846875
transcript.pyannote[143].speaker SPEAKER_03
transcript.pyannote[143].start 754.56284375
transcript.pyannote[143].end 759.10221875
transcript.pyannote[144].speaker SPEAKER_03
transcript.pyannote[144].start 759.50721875
transcript.pyannote[144].end 761.43096875
transcript.pyannote[145].speaker SPEAKER_03
transcript.pyannote[145].start 762.66284375
transcript.pyannote[145].end 769.31159375
transcript.pyannote[146].speaker SPEAKER_03
transcript.pyannote[146].start 770.52659375
transcript.pyannote[146].end 770.96534375
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 770.96534375
transcript.pyannote[147].end 779.41971875
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 779.82471875
transcript.pyannote[148].end 781.02284375
transcript.pyannote[149].speaker SPEAKER_03
transcript.pyannote[149].start 781.02284375
transcript.pyannote[149].end 797.89784375
transcript.pyannote[150].speaker SPEAKER_03
transcript.pyannote[150].start 798.16784375
transcript.pyannote[150].end 798.97784375
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 798.97784375
transcript.pyannote[151].end 799.02846875
transcript.pyannote[152].speaker SPEAKER_03
transcript.pyannote[152].start 799.02846875
transcript.pyannote[152].end 803.17971875
transcript.pyannote[153].speaker SPEAKER_03
transcript.pyannote[153].start 803.39909375
transcript.pyannote[153].end 804.96846875
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 804.96846875
transcript.pyannote[154].end 805.13721875
transcript.pyannote[155].speaker SPEAKER_02
transcript.pyannote[155].start 806.28471875
transcript.pyannote[155].end 808.56284375
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 808.90034375
transcript.pyannote[156].end 811.27971875
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 811.87034375
transcript.pyannote[157].end 828.07034375
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 829.87596875
transcript.pyannote[158].end 835.96784375
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 837.18284375
transcript.pyannote[159].end 840.62534375
transcript.pyannote[160].speaker SPEAKER_02
transcript.pyannote[160].start 841.14846875
transcript.pyannote[160].end 842.58284375
transcript.pyannote[161].speaker SPEAKER_02
transcript.pyannote[161].start 843.22409375
transcript.pyannote[161].end 844.74284375
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 844.75971875
transcript.pyannote[162].end 845.31659375
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 846.10971875
transcript.pyannote[163].end 847.67909375
transcript.pyannote[164].speaker SPEAKER_02
transcript.pyannote[164].start 848.23596875
transcript.pyannote[164].end 851.42534375
transcript.pyannote[165].speaker SPEAKER_02
transcript.pyannote[165].start 851.94846875
transcript.pyannote[165].end 857.85471875
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 858.17534375
transcript.pyannote[166].end 859.87971875
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 861.14534375
transcript.pyannote[167].end 861.17909375
transcript.pyannote[168].speaker SPEAKER_03
transcript.pyannote[168].start 861.17909375
transcript.pyannote[168].end 862.73159375
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 863.01846875
transcript.pyannote[169].end 863.03534375
transcript.pyannote[170].speaker SPEAKER_03
transcript.pyannote[170].start 863.03534375
transcript.pyannote[170].end 863.37284375
transcript.pyannote[171].speaker SPEAKER_03
transcript.pyannote[171].start 864.01409375
transcript.pyannote[171].end 866.91659375
transcript.pyannote[172].speaker SPEAKER_03
transcript.pyannote[172].start 867.38909375
transcript.pyannote[172].end 868.72221875
transcript.pyannote[173].speaker SPEAKER_03
transcript.pyannote[173].start 869.41409375
transcript.pyannote[173].end 872.87346875
transcript.whisperx[0].start 2.998
transcript.whisperx[0].end 4.761
transcript.whisperx[0].text 我們下一位請蘇昭偉詢答請謝謝主席我請我們副審計長跟副組計長
transcript.whisperx[1].start 32.392
transcript.whisperx[1].end 56.329
transcript.whisperx[1].text 主席總署嘛 你是行政議員是你副審議長 你是鑑產議員今天在這裡說鑑產議員 鑑產議員你就是鑑產議員 你都這樣撒來撒去好 我們這個預算編列到預算執行到結算之後我要請問主席處你們的 主席總署你們的角色是什麼
transcript.whisperx[2].start 58.005
transcript.whisperx[2].end 76.665
transcript.whisperx[2].text 跟我們報告就是說基本上從預算籌編開始那我們就是會請各部會來提需求那我們就是會進行會診那會再區分他如果是屬於公共建設科技等等會有一些先期
transcript.whisperx[3].start 78.026
transcript.whisperx[3].end 101.599
transcript.whisperx[3].text 計畫的這個審議機關像國發會科科技部等等那最後我們就把這個會診的結果經過一個會議審查以後提報到行政院院會院會通過以後就送立法院大概我們的角色是這樣所以你們是先前譬如說明年115年的預算你們現在就開始在張羅嗎那你們開始邊邊邊你們是負責前半段嗎
transcript.whisperx[4].start 106.104
transcript.whisperx[4].end 126.807
transcript.whisperx[4].text 那各個部會怎麼編怎麼編 這樣嘛後來大家上行政院 院會後通過 再上過來立法院嘛那立法院審查像這次有一些凍結的 有一些核酸的那你們再報回去之後 請問你們是怎麼分配
transcript.whisperx[5].start 127.935
transcript.whisperx[5].end 141.022
transcript.whisperx[5].text 我看那邊主席長都在哀哀說什麼沒辦法分配沒辦法凍結的他沒有辦法分配到底這是怎麼一回事你要講清楚因為沒有多少人聽得懂
transcript.whisperx[6].start 141.941
transcript.whisperx[6].end 142.621
transcript.whisperx[6].text 所以你就卡在哪裡?
transcript.whisperx[7].start 169.591
transcript.whisperx[7].end 196.325
transcript.whisperx[7].text 因為那個就業部長我在高鐵上跟他同車他也一直在抱怨說統三下來的錢到底我分到多少是不是這樣所以他也不曉得要怎麼做行政院也不曉得要怎麼做是不是這樣就是對目前就是有一個636億不明確是要刪減什麼項目好那你現在互利也沒有過了那你們現在怎麼辦
transcript.whisperx[8].start 198.962
transcript.whisperx[8].end 227.135
transcript.whisperx[8].text 現在基本上就是說就跟那個剛剛部長講的是一樣的問題嘛那種有的刪有的動那再來就3到600多億那個怎麼分法定部要分到多少要分到多少是不是這樣就是跟委員報告就是因為這個636億的不確定性就連動到後面要採取什麼的措施就變成一種困難
transcript.whisperx[9].start 228.2
transcript.whisperx[9].end 233.932
transcript.whisperx[9].text 所以現在已經四月了 你們現在怎麼辦因為六百多一直還是不確定所以勒
transcript.whisperx[10].start 239.844
transcript.whisperx[10].end 247.027
transcript.whisperx[10].text 所以現在就是說我一直叫勞動部叫衛務部趕快來申請解凍但是解凍是另外一個啦這個600多億是統3的嘛是不是要講清楚喔對就是900多億裡面有明確項目的扣除以後還有636億是不明確所以是3的嘛是3減的部分
transcript.whisperx[11].start 269.157
transcript.whisperx[11].end 270.1
transcript.whisperx[11].text 所以這張卡在這裡不知道要怎麼錄是好那
transcript.whisperx[12].start 274.715
transcript.whisperx[12].end 297.621
transcript.whisperx[12].text 審計部你的感受是什麼跟委員報告就是大院審議中央政府總預算案通過了像總統如果公佈之後他們各部會就會把那個每個月的分配預算都會分配分配之後審計部的主要的職長之一就是會監督預算執行
transcript.whisperx[13].start 302.162
transcript.whisperx[13].end 315.167
transcript.whisperx[13].text 從這個會計年度一開始到結束我們都是包括平常的會計報告的審核分配預算的查核到實際的派員就地去財務搜索抽查另外一部分是專案調查
transcript.whisperx[14].start 316.707
transcript.whisperx[14].end 327.743
transcript.whisperx[14].text 所以你114年的預算現在互裔也沒過了所以呢現在總統府也公佈了所以你是114年按頁
transcript.whisperx[15].start 330.902
transcript.whisperx[15].end 357.805
transcript.whisperx[15].text 跟攤每個月都有在追蹤考核是這樣嗎每個月都有審核還是等到115年都不料啊我們的審核包括書面審核書面審核就平常破櫃資訊系統跟機關送過來的會計報告我們也會線上去看他的交易憑證這個是平常就在做然後也要例行派員到各部會去就地抽查
transcript.whisperx[16].start 359.126
transcript.whisperx[16].end 382.261
transcript.whisperx[16].text 這個是從年頭到年尾都好那剛剛主計處那邊講的600多億未定那你們怎麼弄我們根據他確定的就是他們確定的不會確定的我們根據那個數字來所以主計處你現在那個600多億你說未定你們現在要怎麼談你還沒有ideaI have no idea
transcript.whisperx[17].start 383.34
transcript.whisperx[17].end 411.014
transcript.whisperx[17].text 就是說因為這個不確定涉及到行政跟立法的這個部分所以變成他沒有辦法透過行政部門這一邊獨立去解決這個問題所以這個變成說可能就必須有看是不是透過進一步的協商還是什麼就必須行政立法再度的來處理這個問題好 了解好 那你們兩個請回吧部長 瑪莉亞
transcript.whisperx[18].start 421.338
transcript.whisperx[18].end 449.255
transcript.whisperx[18].text 書人好今天要講的這個題目事實上也不是你任上花生的啦這是去年甚至前年的事情那你是一個政務官嘛那你講白一點你拍拍屁股就可以走人啦對不對所以受苦受難的是我們勞動部這些事務官公務人員我覺得他們是很辛苦的他們的士氣蠻低迷的
transcript.whisperx[19].start 450.575
transcript.whisperx[19].end 462.001
transcript.whisperx[19].text 那你大家又有人搶 你有在搶嗎 我不知道啦搶那個公園是我們部裡面最重要的資產
transcript.whisperx[20].start 463.359
transcript.whisperx[20].end 490.186
transcript.whisperx[20].text 沒有 公務人員是我們的資產 國家的財產我們都要疼惜啦這個是不管藍執政 不管綠執政這些公務人員他們都是要幹到退休的那我是一直覺得我們公務人員好不容易拆車拆到要死然後課高考 課特考 課薪水那麼低來這邊天天被罵 我是覺得那是我不太想幹啦
transcript.whisperx[21].start 491.906
transcript.whisperx[21].end 518.813
transcript.whisperx[21].text 真的真的所以我們要跟他們加油啦跟他們打氣那因為以前真的是有點脫序那現在你來就更嚴格所以一磚一瓦都管得那麼嚴我是覺得有時候也要檢討啦也是要幫他練的啦一陣緊一陣鬆另外也是一樣啦所以我建議就是好好的來
transcript.whisperx[22].start 522.053
transcript.whisperx[22].end 534.96
transcript.whisperx[22].text 檢討檢討啦我看你從上任到現在都非常戰爭津津啊我有問你好幾次啊你說你都用那個聖上仙術在維持我不曉得真的還假的
transcript.whisperx[23].start 536.496
transcript.whisperx[23].end 562.777
transcript.whisperx[23].text 好我問一個我們現在救援基金現在是現在有多少錢現在目前有400多億那這一次這個美國川普這樣亂搞那我們已經很多有中部的一些譬如說紡織的或者是做螺絲的他們已經被美國的客戶已經通知說先不要出貨三個月
transcript.whisperx[24].start 564.128
transcript.whisperx[24].end 568.012
transcript.whisperx[24].text 我現在問說要不要出路三個,大家就不理我不慷慨了嘛馬上出問題啊
transcript.whisperx[25].start 572.946
transcript.whisperx[25].end 592.923
transcript.whisperx[25].text 那換無薪假也罷 領半薪也罷你們現在是打算怎麼去幫助這些勞工 這個最實際喔跟蘇緯說明喔 確實在這個禮拜裡面陸陸續續其實聽到一些來自包括美國的進口商跟我們台灣的製造商或出口商開始有一些在討論訂單上面的變動的狀況 這是有的
transcript.whisperx[26].start 596.306
transcript.whisperx[26].end 623.317
transcript.whisperx[26].text 那當然下一步會看這一些台灣的廠商他有些他可能會調動他的產線有些他可能會做他自己內部上面相關排班的調整可是我要說的是說我們是很不希望是走到比方說會是解雇的這個狀況或者是大量解雇那我們當然也會我們會在相關的機制上面做一些把關我們也不希望企業來濫用像這個減班休息的做法
transcript.whisperx[27].start 625.092
transcript.whisperx[27].end 638.191
transcript.whisperx[27].text 俗稱減班休息有人會俗稱無薪假可是他並不是真的無薪因為台灣的減班休息其實都是要還是要給最低工資的那是要給最低工資但是如果最低工資這一段你們有沒有補沒有
transcript.whisperx[28].start 641.454
transcript.whisperx[28].end 664.421
transcript.whisperx[28].text 如果有準備休息的狀況的話我們其實有相對應包括像充電才出發或者是有一些包括像雇用安定的措施來可能可以來去協助這個勞工他在收入上面的做法我們其實過去是有包括疫情的時候金融海嘯的時候是有這樣的經驗那我們也把過去的這些措施這些措施都還在
transcript.whisperx[29].start 664.901
transcript.whisperx[29].end 686.13
transcript.whisperx[29].text 但我們也在規劃一個更針對目前關稅因應關稅的版本來去更清楚的因地制宜或者是來去設定現有的情境下面怎麼樣包括它的適用範圍甚至會不會在某些部分需要支持力度的加碼其實我們都在目前在做一個這樣子量身訂做的設定
transcript.whisperx[30].start 688.211
transcript.whisperx[30].end 696.259
transcript.whisperx[30].text 好 那我們百姓 共和國一般民眾的情感每次都在問你這次要怎麼退回來我是認為 像這個是
transcript.whisperx[31].start 705.031
transcript.whisperx[31].end 731.448
transcript.whisperx[31].text 再出發的這個是乍臨的 再下一張你要去追這些錢回來勢必要有有憑有據嘛你不能說你部長想說要跟人家賺錢 你是平常要跟人家賺錢所以一定要 換你判斷說他有安若端有福利或是說有總保私囊這個一定要判決你才能辦法去要嘛 對不對 部長是不是這樣我們如果要跟個人
transcript.whisperx[32].start 732.669
transcript.whisperx[32].end 761.258
transcript.whisperx[32].text 包括甚至包括決策者要去做相關的追究或追討的話當然要有法律上面的依據他如果沒有把錢放在自己的口袋裡面你會說他是圖利啊怎麼樣不然的話你要去最後要去把他追錢窩香沒有那麼簡單耶所以就是看說還是要看有沒有法律上面的依據如果有這個法律上的依據的話那當然該怎麼做就要怎麼做啊
transcript.whisperx[33].start 762.708
transcript.whisperx[33].end 769.001
transcript.whisperx[33].text 可是前提是所以這是為什麼我們說我們會來配合檢調或司法的結果來做相關的追究
transcript.whisperx[34].start 770.758
transcript.whisperx[34].end 797.383
transcript.whisperx[34].text 像陳基普講的說要等到他判刑現在都起訴嘛起訴之後一審、二審、三審要不然到底判定沒有兩三年搞不定啦就我們目前看到檢調的起訴書上面的內容的話如果剛才蘇緣講的是謝前分署長的狀況的話看起來他在檢調寫的上面他已經把他不罰所得其實已經有返還了
transcript.whisperx[35].start 798.22
transcript.whisperx[35].end 801.37
transcript.whisperx[35].text 好像有一百萬拿多少就繳出去應該不是這個數字兩萬多塊
transcript.whisperx[36].start 806.488
transcript.whisperx[36].end 827.973
transcript.whisperx[36].text 所以那個前部長 前前部長跟鋁派界定我看他只有唱歌而已啊我看他沒有幹瑕事啊所以那個要怎麼去追尋我是覺得大家情感歸情感啦不然還是要回歸講道理跟回歸法治面啦所以法務部 那個那個 審計部叫你要從邊或者怎麼樣這個也都可以理解啦
transcript.whisperx[37].start 837.393
transcript.whisperx[37].end 858.855
transcript.whisperx[37].text 不過汪洋普勞你往後的要更嚴格我認為你是不會你是很嚴的像現在這種脫序的行為我是當然是不對啦所以我再次的跟我們勞動部我們公務員加油然後要請部長
transcript.whisperx[38].start 864.099
transcript.whisperx[38].end 869.523
transcript.whisperx[38].text 我會很謝謝我們公務的同仁因為他們是最辛苦的謝謝好 謝謝蘇青委員的發言謝謝部長的答案