iVOD / 159238

Field Value
IVOD_ID 159238
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/159238
日期 2025-03-17
會議資料.會議代碼 委員會-11-3-23-3
會議資料.會議代碼:str 第11屆第3會期交通委員會第3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 3
會議資料.種類 委員會
會議資料.委員會代碼[0] 23
會議資料.委員會代碼:str[0] 交通委員會
會議資料.標題 第11屆第3會期交通委員會第3次全體委員會議
影片種類 Clip
開始時間 2025-03-17T11:10:08+08:00
結束時間 2025-03-17T11:22:56+08:00
影片長度 00:12:48
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/597499b2503050fb23c622125da3c988fc70f51a359b58cfeba1aea0cf818e9185ef96e8213ea40c5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 蔡其昌
委員發言時間 11:10:08 - 11:22:56
會議時間 2025-03-17T09:00:00+08:00
會議名稱 立法院第11屆第3會期交通委員會第3次全體委員會議(事由:邀請行政院公共工程委員會主任委員陳金德列席報告業務概況,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 3.00096875
transcript.pyannote[0].end 3.64221875
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 4.16534375
transcript.pyannote[1].end 9.04221875
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 14.52659375
transcript.pyannote[2].end 15.26909375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 16.06221875
transcript.pyannote[3].end 17.02409375
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 18.30659375
transcript.pyannote[4].end 19.67346875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 20.11221875
transcript.pyannote[5].end 21.49596875
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 22.00221875
transcript.pyannote[6].end 23.03159375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 23.97659375
transcript.pyannote[7].end 26.54159375
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 27.03096875
transcript.pyannote[8].end 29.39346875
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 29.95034375
transcript.pyannote[9].end 36.29534375
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 36.63284375
transcript.pyannote[10].end 39.24846875
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 39.63659375
transcript.pyannote[11].end 41.23971875
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 41.79659375
transcript.pyannote[12].end 44.19284375
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 44.96909375
transcript.pyannote[13].end 45.28971875
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 46.21784375
transcript.pyannote[14].end 46.50471875
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 48.27659375
transcript.pyannote[15].end 49.17096875
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 49.74471875
transcript.pyannote[16].end 51.80346875
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 51.88784375
transcript.pyannote[17].end 52.64721875
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 52.91721875
transcript.pyannote[18].end 53.84534375
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 54.55409375
transcript.pyannote[19].end 58.46909375
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 58.84034375
transcript.pyannote[20].end 68.59409375
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 69.26909375
transcript.pyannote[21].end 71.64846875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 71.93534375
transcript.pyannote[22].end 72.86346875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 73.55534375
transcript.pyannote[23].end 78.26346875
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 79.30971875
transcript.pyannote[24].end 80.69346875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 81.19971875
transcript.pyannote[25].end 81.72284375
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 82.46534375
transcript.pyannote[26].end 83.46096875
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 84.10221875
transcript.pyannote[27].end 85.90784375
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 86.75159375
transcript.pyannote[28].end 87.44346875
transcript.pyannote[29].speaker SPEAKER_01
transcript.pyannote[29].start 88.52346875
transcript.pyannote[29].end 89.43471875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 90.31221875
transcript.pyannote[30].end 92.43846875
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 93.58596875
transcript.pyannote[31].end 94.19346875
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 94.76721875
transcript.pyannote[32].end 95.37471875
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 96.06659375
transcript.pyannote[33].end 99.57659375
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 100.16721875
transcript.pyannote[34].end 102.05721875
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 102.66471875
transcript.pyannote[35].end 104.36909375
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 105.56721875
transcript.pyannote[36].end 108.16596875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 108.77346875
transcript.pyannote[37].end 109.53284375
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 110.15721875
transcript.pyannote[38].end 112.70534375
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 113.22846875
transcript.pyannote[39].end 115.01721875
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 115.47284375
transcript.pyannote[40].end 117.44721875
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 117.81846875
transcript.pyannote[41].end 121.07534375
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 122.45909375
transcript.pyannote[42].end 127.67346875
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 128.39909375
transcript.pyannote[43].end 131.87534375
transcript.pyannote[44].speaker SPEAKER_01
transcript.pyannote[44].start 132.58409375
transcript.pyannote[44].end 132.87096875
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 133.54596875
transcript.pyannote[45].end 134.65971875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 135.36846875
transcript.pyannote[46].end 140.36346875
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 140.75159375
transcript.pyannote[47].end 142.10159375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 143.13096875
transcript.pyannote[48].end 145.54409375
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 146.65784375
transcript.pyannote[49].end 148.66596875
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 149.15534375
transcript.pyannote[50].end 150.04971875
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 151.16346875
transcript.pyannote[51].end 152.59784375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 152.85096875
transcript.pyannote[52].end 157.23846875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 157.55909375
transcript.pyannote[53].end 159.06096875
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 159.78659375
transcript.pyannote[54].end 163.21221875
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 164.34284375
transcript.pyannote[55].end 164.89971875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 165.72659375
transcript.pyannote[56].end 175.14284375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 175.26096875
transcript.pyannote[57].end 179.49659375
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 180.30659375
transcript.pyannote[58].end 181.55534375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 181.84221875
transcript.pyannote[59].end 183.46221875
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 184.62659375
transcript.pyannote[60].end 185.11596875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 185.36909375
transcript.pyannote[61].end 186.01034375
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 186.66846875
transcript.pyannote[62].end 187.09034375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 188.32221875
transcript.pyannote[63].end 190.36409375
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 191.02221875
transcript.pyannote[64].end 195.25784375
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 195.51096875
transcript.pyannote[65].end 197.08034375
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 197.75534375
transcript.pyannote[66].end 199.76346875
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 200.47221875
transcript.pyannote[67].end 202.42971875
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 203.89784375
transcript.pyannote[68].end 204.89346875
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 205.28159375
transcript.pyannote[69].end 205.88909375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 206.69909375
transcript.pyannote[70].end 210.63096875
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 211.05284375
transcript.pyannote[71].end 212.90909375
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 214.49534375
transcript.pyannote[72].end 215.38971875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 215.96346875
transcript.pyannote[73].end 216.52034375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 217.33034375
transcript.pyannote[74].end 218.24159375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 218.96721875
transcript.pyannote[75].end 220.03034375
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 220.77284375
transcript.pyannote[76].end 224.97471875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 225.64971875
transcript.pyannote[77].end 225.95346875
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 226.71284375
transcript.pyannote[78].end 233.39534375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 233.59784375
transcript.pyannote[79].end 234.01971875
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 234.39096875
transcript.pyannote[80].end 237.52971875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 238.30596875
transcript.pyannote[81].end 240.28034375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 240.48284375
transcript.pyannote[82].end 242.32221875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 242.65971875
transcript.pyannote[83].end 248.80221875
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 249.66284375
transcript.pyannote[84].end 251.36721875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 251.77221875
transcript.pyannote[85].end 252.32909375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 253.07159375
transcript.pyannote[86].end 253.99971875
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 254.48909375
transcript.pyannote[87].end 255.50159375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 255.72096875
transcript.pyannote[88].end 260.26034375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 260.42909375
transcript.pyannote[89].end 261.35721875
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 261.72846875
transcript.pyannote[90].end 265.10346875
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 265.33971875
transcript.pyannote[91].end 276.93284375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 277.37159375
transcript.pyannote[92].end 278.55284375
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 279.04221875
transcript.pyannote[93].end 280.42596875
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 281.05034375
transcript.pyannote[94].end 287.69909375
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 288.47534375
transcript.pyannote[95].end 291.39471875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 292.74471875
transcript.pyannote[96].end 293.79096875
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 294.33096875
transcript.pyannote[97].end 299.25846875
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 299.66346875
transcript.pyannote[98].end 303.03846875
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 303.49409375
transcript.pyannote[99].end 304.99596875
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 305.46846875
transcript.pyannote[100].end 316.84221875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 311.07096875
transcript.pyannote[101].end 311.37471875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 317.04471875
transcript.pyannote[102].end 318.58034375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 318.81659375
transcript.pyannote[103].end 322.68096875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 322.93409375
transcript.pyannote[104].end 328.97534375
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 329.39721875
transcript.pyannote[105].end 331.87784375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 332.23221875
transcript.pyannote[106].end 338.83034375
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 339.13409375
transcript.pyannote[107].end 340.51784375
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 341.10846875
transcript.pyannote[108].end 348.53346875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 348.73596875
transcript.pyannote[109].end 350.64284375
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 350.82846875
transcript.pyannote[110].end 353.32596875
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 353.56221875
transcript.pyannote[111].end 355.11471875
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 355.31721875
transcript.pyannote[112].end 357.03846875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 357.32534375
transcript.pyannote[113].end 362.74221875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 363.01221875
transcript.pyannote[114].end 364.58159375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 364.73346875
transcript.pyannote[115].end 368.51346875
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 369.27284375
transcript.pyannote[116].end 386.08034375
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 386.38409375
transcript.pyannote[117].end 387.49784375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 387.58221875
transcript.pyannote[118].end 390.41721875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 390.85596875
transcript.pyannote[119].end 399.02346875
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 399.24284375
transcript.pyannote[120].end 416.67471875
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 417.21471875
transcript.pyannote[121].end 424.94346875
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 424.99409375
transcript.pyannote[122].end 427.82909375
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 428.52096875
transcript.pyannote[123].end 430.29284375
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 430.64721875
transcript.pyannote[124].end 434.66346875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 435.28784375
transcript.pyannote[125].end 445.51409375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 445.81784375
transcript.pyannote[126].end 453.17534375
transcript.pyannote[127].speaker SPEAKER_02
transcript.pyannote[127].start 453.17534375
transcript.pyannote[127].end 454.50846875
transcript.pyannote[128].speaker SPEAKER_02
transcript.pyannote[128].start 454.87971875
transcript.pyannote[128].end 469.15596875
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 462.87846875
transcript.pyannote[129].end 463.68846875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 463.94159375
transcript.pyannote[130].end 463.97534375
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 468.91971875
transcript.pyannote[131].end 474.69096875
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 475.24784375
transcript.pyannote[132].end 475.56846875
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 475.97346875
transcript.pyannote[133].end 477.67784375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 478.13346875
transcript.pyannote[134].end 486.65534375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 487.44846875
transcript.pyannote[135].end 489.42284375
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 490.55346875
transcript.pyannote[136].end 493.42221875
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 494.01284375
transcript.pyannote[137].end 504.91409375
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 505.52159375
transcript.pyannote[138].end 523.02096875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 523.64534375
transcript.pyannote[139].end 525.90659375
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 526.37909375
transcript.pyannote[140].end 531.50909375
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 532.08284375
transcript.pyannote[141].end 540.01409375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 540.73971875
transcript.pyannote[142].end 547.67534375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 549.32909375
transcript.pyannote[143].end 558.49221875
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 559.42034375
transcript.pyannote[144].end 589.05284375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 589.13721875
transcript.pyannote[145].end 591.87096875
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 592.39409375
transcript.pyannote[146].end 594.67221875
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 595.02659375
transcript.pyannote[147].end 599.02596875
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 599.17784375
transcript.pyannote[148].end 599.88659375
transcript.pyannote[149].speaker SPEAKER_02
transcript.pyannote[149].start 600.46034375
transcript.pyannote[149].end 604.56096875
transcript.pyannote[150].speaker SPEAKER_02
transcript.pyannote[150].start 604.67909375
transcript.pyannote[150].end 612.45846875
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 612.55971875
transcript.pyannote[151].end 614.02784375
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 614.26409375
transcript.pyannote[152].end 615.19221875
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 615.71534375
transcript.pyannote[153].end 616.05284375
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 616.49159375
transcript.pyannote[154].end 617.77409375
transcript.pyannote[155].speaker SPEAKER_02
transcript.pyannote[155].start 618.01034375
transcript.pyannote[155].end 620.03534375
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 620.17034375
transcript.pyannote[156].end 627.81471875
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 628.08471875
transcript.pyannote[157].end 632.03346875
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 632.30346875
transcript.pyannote[158].end 632.62409375
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 632.87721875
transcript.pyannote[159].end 638.14221875
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 638.27721875
transcript.pyannote[160].end 653.92034375
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 654.25784375
transcript.pyannote[161].end 661.63221875
transcript.pyannote[162].speaker SPEAKER_00
transcript.pyannote[162].start 659.15159375
transcript.pyannote[162].end 659.20221875
transcript.pyannote[163].speaker SPEAKER_01
transcript.pyannote[163].start 662.07096875
transcript.pyannote[163].end 663.45471875
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 663.85971875
transcript.pyannote[164].end 673.46159375
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 673.93409375
transcript.pyannote[165].end 678.54096875
transcript.pyannote[166].speaker SPEAKER_01
transcript.pyannote[166].start 678.96284375
transcript.pyannote[166].end 693.01971875
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 695.11221875
transcript.pyannote[167].end 697.03596875
transcript.pyannote[168].speaker SPEAKER_02
transcript.pyannote[168].start 697.20471875
transcript.pyannote[168].end 698.77409375
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 698.99346875
transcript.pyannote[169].end 701.71034375
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 702.08159375
transcript.pyannote[170].end 707.16096875
transcript.pyannote[171].speaker SPEAKER_01
transcript.pyannote[171].start 707.56596875
transcript.pyannote[171].end 709.30409375
transcript.pyannote[172].speaker SPEAKER_01
transcript.pyannote[172].start 709.94534375
transcript.pyannote[172].end 711.29534375
transcript.pyannote[173].speaker SPEAKER_01
transcript.pyannote[173].start 711.61596875
transcript.pyannote[173].end 711.95346875
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 715.39596875
transcript.pyannote[174].end 715.54784375
transcript.pyannote[175].speaker SPEAKER_00
transcript.pyannote[175].start 716.47596875
transcript.pyannote[175].end 731.61284375
transcript.pyannote[176].speaker SPEAKER_01
transcript.pyannote[176].start 725.09909375
transcript.pyannote[176].end 725.31846875
transcript.pyannote[177].speaker SPEAKER_01
transcript.pyannote[177].start 731.96721875
transcript.pyannote[177].end 735.86534375
transcript.pyannote[178].speaker SPEAKER_02
transcript.pyannote[178].start 735.88221875
transcript.pyannote[178].end 738.22784375
transcript.pyannote[179].speaker SPEAKER_01
transcript.pyannote[179].start 738.44721875
transcript.pyannote[179].end 741.18096875
transcript.pyannote[180].speaker SPEAKER_02
transcript.pyannote[180].start 740.72534375
transcript.pyannote[180].end 748.38659375
transcript.pyannote[181].speaker SPEAKER_01
transcript.pyannote[181].start 741.95721875
transcript.pyannote[181].end 742.53096875
transcript.pyannote[182].speaker SPEAKER_02
transcript.pyannote[182].start 748.55534375
transcript.pyannote[182].end 750.34409375
transcript.pyannote[183].speaker SPEAKER_02
transcript.pyannote[183].start 750.52971875
transcript.pyannote[183].end 759.67596875
transcript.pyannote[184].speaker SPEAKER_01
transcript.pyannote[184].start 756.63846875
transcript.pyannote[184].end 765.26159375
transcript.pyannote[185].speaker SPEAKER_02
transcript.pyannote[185].start 762.86534375
transcript.pyannote[185].end 763.89471875
transcript.pyannote[186].speaker SPEAKER_01
transcript.pyannote[186].start 765.86909375
transcript.pyannote[186].end 766.12221875
transcript.pyannote[187].speaker SPEAKER_02
transcript.pyannote[187].start 766.99971875
transcript.pyannote[187].end 768.24846875
transcript.whisperx[0].start 4.853
transcript.whisperx[0].end 20.801
transcript.whisperx[0].text 謝謝主席 請陳主委好 陳主委主委早這個主委預算刪除凍結這麼嚴重
transcript.whisperx[1].start 24.048
transcript.whisperx[1].end 44
transcript.whisperx[1].text 其實本席在質詢裡也有點辛苦啦因為涉及到預算的我都不問了啦你就沒錢我自己問一半是在問什麼所以如果我待會不小心還有問到跟預算有關係你就直接告訴本席說報告委員預算被動或者被刪所以沒辦法執行好
transcript.whisperx[2].start 48.703
transcript.whisperx[2].end 53.63
transcript.whisperx[2].text 這個預算啦這個送院會解凍這個本席也沒有
transcript.whisperx[3].start 54.639
transcript.whisperx[3].end 80.214
transcript.whisperx[3].text 印象中也很少聽到這樣子解凍就在委員會現在這個可能要請議事處再研議看看送院會解凍的程序到底是要不要交付委員會先審再回送給院會來審這個可能大院要去研究一下因為至少在我印象裡面好像送院會解凍這個
transcript.whisperx[4].start 82.523
transcript.whisperx[4].end 101.119
transcript.whisperx[4].text 不知道,不管先回到我們的主題這個工程會,我的辦公室有問了一下最近大家都在做這個發包,都在做這個減項就做這個減項招標這個減項招標,都是因應著物價上漲
transcript.whisperx[5].start 108.817
transcript.whisperx[5].end 134.202
transcript.whisperx[5].text 那因為中央政府要地方政府要經費不足嘛那經費不足的情況底下事情很重要又要做所以呢我們就把它做減相的發包那這個減相發包本來本席就覺得這個問題很大因為等於是我們錢還不一定夠但菜都先點了
transcript.whisperx[6].start 135.407
transcript.whisperx[6].end 159.902
transcript.whisperx[6].text 那我們是預期反正一邊吃錢還會有人送過來餐廳所以我們就繼續吃那現在問題更嚴重的原因是因為我們原先帶來的錢又被刪除本來已經帶夠了但因為這個其他因素又把我們帶來餐廳要吃飯的錢又凍結又刪除所以這個減項發包的問題會越來越嚴重那
transcript.whisperx[7].start 165.779
transcript.whisperx[7].end 182.487
transcript.whisperx[7].text 工程會這邊有提出這個減向發包這個主要還是因為大概有九成都是因為物價上漲這個沒有足夠的經費所以我們做這樣的一個調整那減向發包最後就會發現幾個問題譬如說這個台北中校橋
transcript.whisperx[8].start 191.349
transcript.whisperx[8].end 219.674
transcript.whisperx[8].text 這個引橋拆除兩次流標那北市要檢向發包那這個檢向發包啊有沒有可能會出現這個有橋沒有路燈那像我們這個啊台中啊像大甲國中啊這個手球啊手球館它檢向發包的結果就是房子蓋好了裡面不可以打手球而且沒有門
transcript.whisperx[9].start 220.814
transcript.whisperx[9].end 248.387
transcript.whisperx[9].text 沒有門 因為門當時檢像發包所以沒有門所以檢像發包它會產生我認為它會有一些問題譬如說報紙也看到醫院蓋但檢像發包所以醫院沒有防火門所以這個檢像發包的問題主委 這個的確是應該要認真工程會恐怕要認真來講否則以後這個案例會越來越多而且越來越荒謬
transcript.whisperx[10].start 249.704
transcript.whisperx[10].end 276.755
transcript.whisperx[10].text 就不久之後我們就會看到這個本來檢向了那本來預期這個今年要補結果預算又被刪又被凍所以不能補不能補就會發現就會出現很多很荒謬的建築物或者很荒謬的案例我剛剛已經舉了幾個啦比如說我們手球場沒有門的啦譬如說可能蓋路橋沒路燈的啦譬如說醫院沒有防火門的啦
transcript.whisperx[11].start 277.795
transcript.whisperx[11].end 289.445
transcript.whisperx[11].text 那我相信會越來越多所以這個要不要工程會要不要有一個統一性的指示對於檢像發包到底要怎麼來規範才不會出現這種亂象
transcript.whisperx[12].start 294.415
transcript.whisperx[12].end 309.473
transcript.whisperx[12].text 剪相發包那當然也是目前政府採購法裡面這個有規範的一個發包方式那有時候是因為比方說這個原設計的費用跟他預期能夠獲得中央的補助
transcript.whisperx[13].start 310.174
transcript.whisperx[13].end 328.526
transcript.whisperx[13].text 有所落差或者是他獲得議會同意的預算有所落差那在不影響主要的這個工程的核心核心需求之下那麼去檢向發包那未來他有機會再擴充可能中央也同意說
transcript.whisperx[14].start 329.506
transcript.whisperx[14].end 349.326
transcript.whisperx[14].text 夏年度或以後年度一定會給你那這種情形有時候是有在進行但是至於把主要的核心的價值不考慮那麼在預算還沒有確定的狀況之下做了一些比較不符合常規的減向花包那這部分的確工程會的確要來檢討
transcript.whisperx[15].start 350.948
transcript.whisperx[15].end 368.169
transcript.whisperx[15].text 那把這些太陽啊列為一個相對的教材那麼韓班各機關那麼對檢像花苞這件事情應該有一些負面表列要避開的這一類我們會同意蔡委員的這個主張我們會立即來改善
transcript.whisperx[16].start 369.332
transcript.whisperx[16].end 398.321
transcript.whisperx[16].text 好 謝謝主委啦 應該要有一些規範啦沒有規範 譬如說你要什麼樣的前提底下你減相發包是可以的什麼樣的狀況底下是不可以的譬如說什麼美術館減相發包那完工後還需要20億結果可能完工後沒有辦法使用就是殼子蓋好在裡面可能沒錢嘛那我的意思是說這個本來就算預算沒有被動被刪也可能會發生
transcript.whisperx[17].start 399.361
transcript.whisperx[17].end 427.717
transcript.whisperx[17].text 就大家地方政府可能搶著 要有政績嘛就轉到花包出去了結果呢 什麼東西卡好卡好內容就沒有辦法所以會有很多那種案子就是奇怪大家看殼都已經蓋好了 為什麼遲遲不能使用那本席的意思就是說今年啊因為又預算遇到這個把中央的預算動成這樣 砍成這個樣子那所以可能這個問題本來就算我承諾你的
transcript.whisperx[18].start 428.564
transcript.whisperx[18].end 445.084
transcript.whisperx[18].text 沒問題我本來可以承諾你結果沒想到沒有發生過預算被人家砍成這個樣子所以可能就沒有辦法承諾了就沒辦法履行那個承諾所以我同意主委啦就是你把它檢討一下就是什麼樣的樣態底下不可以再
transcript.whisperx[19].start 446.285
transcript.whisperx[19].end 474.324
transcript.whisperx[19].text 這樣子的方式去發包就檢像發包應該是要有條件的情況底下才可以進行這個檢像發包另外就是如果檢像發包預期要擴充那這個訊息要揭露不能只有單獨幾家知道其他的不知道會擴充而且擴充可能擴充很多所以這訊息是要揭露沒錯因為揭露在標的過程才會公平OK這個我覺得這個建議是很好的
transcript.whisperx[20].start 476.065
transcript.whisperx[20].end 504.553
transcript.whisperx[20].text 第二個我想跟主委請教那個CSR納入評比這個事情看起來公共工程會做的這應該是主計單位吧 審計處做的中央機關大概有三層做CSR的評比就是最有力標啦最有力標有納入CSR的中央大概三層國營事業大概四層地方政府僅有一層
transcript.whisperx[21].start 505.578
transcript.whisperx[21].end 531.336
transcript.whisperx[21].text 那我們都知道CSR你要最有利標我們要意思就是說我們評選 透過評選評選出最好的公司 最優質的公司能力最好的公司那這裡面有很多條件要去審核那這CSR的納入評比的比例這麼低像地方政府只有一成納入那這CSR裡面涉及到工資合不合理嘛薪資結構合不合理
transcript.whisperx[22].start 532.156
transcript.whisperx[22].end 547.434
transcript.whisperx[22].text 那像這樣的一個照顧勞工考量這個勞工的權益的部分這種薪資合理化的這個部分所以有沒有什麼方法或者是未來有什麼計畫讓這個CSR納入評比的比例可以拉升
transcript.whisperx[23].start 549.363
transcript.whisperx[23].end 573.57
transcript.whisperx[23].text 好 謝謝蔡委員那麼我們目前正在整理相關的法規會朝向ESG方向來進行過去我們都講CSR目前因為環境重視所以用ESG當然我們會在評選的部分希望各機關在辦理有利標然後評選的時候
transcript.whisperx[24].start 575.35
transcript.whisperx[24].end 590.925
transcript.whisperx[24].text 有做到一定標準的他應該給他一定的分數來鼓勵企業那包括我們主席很重視的勞工的薪資的部分也都會納入加分的項目不過呢這個ESG或CSR有做沒做還是說做好做壞
transcript.whisperx[25].start 592.472
transcript.whisperx[25].end 614.408
transcript.whisperx[25].text 有時候會差很多啦就有的公司可能那個永續報告寫得很漂亮那事實上沒在做啦所以這裡我們在還在思考用什麼樣的標準比較明確說這個公司他很努力在做ESG或者他已經做了10年了做20年了不是去年才做的那他有沒有像像這個
transcript.whisperx[26].start 617.131
transcript.whisperx[26].end 636.386
transcript.whisperx[26].text 這個經管會或證交所他上市公司有沒有提永續報告這我們就規劃一個比較嚴謹的方式來鼓勵企業重視企業社會責任或者是環境這樣的或者相關的公司治理我們都會來考量這個會遵照蔡委員的交代來重新訂購一個比較嚴謹的標準
transcript.whisperx[27].start 638.348
transcript.whisperx[27].end 661.317
transcript.whisperx[27].text 好 這個主委你也知道問題啦 第一個目標要清楚啦ESG也好 CSI也好 其實都是企業社會責任的指標那這個事情要推 政府再不動就很困難嘛 特別是在有利標但如同主委剛剛講的 也有可能會有公不公平 或者真的有落實嗎 這種疑慮 所以可能
transcript.whisperx[28].start 662.417
transcript.whisperx[28].end 677.842
transcript.whisperx[28].text 評比的百分比或者我們有訂定另外一套去合格查實的這個方法 這個本席都支持那態度先有了後面就會慢慢推動嘛 好不好最後一個 這個
transcript.whisperx[29].start 679.082
transcript.whisperx[29].end 692.085
transcript.whisperx[29].text 本席跟交通部這麼多年來一直在爭取這個我們台中大甲溪橋跟大安溪橋的改建那交通部跟本席講說已經送到工程會來審議那主委你知道這個案子嗎我是請我們這個處長來說明好不好這是屬於基本設計審查
transcript.whisperx[30].start 702.128
transcript.whisperx[30].end 711.934
transcript.whisperx[30].text 就我們台中大甲西橋跟大安西橋年久了嘛現在公路局希望把它本席爭取要改建嘛來可不可以說明一下處長報告委員齁這個案子的改建案交通部已經送到我們工程會來審議齁那目前已經送送往國發會那國發會的現在已經在會診中
transcript.whisperx[31].start 732.434
transcript.whisperx[31].end 735.613
transcript.whisperx[31].text 所以我們預期他的進度大概是怎麼樣
transcript.whisperx[32].start 735.919
transcript.whisperx[32].end 764.35
transcript.whisperx[32].text 那國安會如果審閉行政院就會核定所以基本上等國安會應該很快如果基本設計就是工程會審閉國安會這部分只是一個改建沒有相關的環評或相關的問題國安會審這個會很快所以工程會審了我們審了才會送國安會已經出去了簡單講是這樣子那已經不在你們追案子已經不在工程會了是在國安會了這樣就好了謝謝
transcript.whisperx[33].start 767.026
transcript.whisperx[33].end 767.228
transcript.whisperx[33].text 好 謝謝我們