iVOD / 169936

Field Value
IVOD_ID 169936
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/169936
日期 2026-06-10
會議資料.會議代碼 委員會-11-5-36-18
會議資料.會議代碼:str 第11屆第5會期司法及法制委員會第18次全體委員會議
會議資料.屆 11
會議資料.會期 5
會議資料.會次 18
會議資料.種類 委員會
會議資料.委員會代碼[0] 36
會議資料.委員會代碼:str[0] 司法及法制委員會
會議資料.標題 第11屆第5會期司法及法制委員會第18次全體委員會議
影片種類 Clip
開始時間 2026-06-10T11:34:37+08:00
結束時間 2026-06-10T11:48:56+08:00
影片長度 00:14:19
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/dee24285c0428ea5057edc5e30a022b502c75a4b042dc3678c63d91a868a86b12bfe832c71c1a02f5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 范雲
委員發言時間 11:34:37 - 11:48:56
會議時間 2026-06-10T09:00:00+08:00
會議名稱 立法院第11屆第5會期司法及法制委員會第18次全體委員會議(事由:併案審查 (一)台灣民眾黨黨團擬具「軍公教人員待遇調整條例草案」案。 (二)委員翁曉玲等16人擬具「軍公教人員待遇調整條例草案」案。 【6月10日會議僅進行詢答】 【6月10日及11日兩天一次會】)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 7.38846875
transcript.pyannote[0].end 12.78846875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 15.97784375
transcript.pyannote[1].end 27.28409375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 30.27096875
transcript.pyannote[2].end 30.55784375
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 31.62096875
transcript.pyannote[3].end 32.93721875
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 31.65471875
transcript.pyannote[4].end 32.38034375
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 34.59096875
transcript.pyannote[5].end 37.08846875
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 37.76346875
transcript.pyannote[6].end 38.15159375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 38.43846875
transcript.pyannote[7].end 40.41284375
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 40.61534375
transcript.pyannote[8].end 48.29346875
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 48.85034375
transcript.pyannote[9].end 49.18784375
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 49.42409375
transcript.pyannote[10].end 52.74846875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 52.95096875
transcript.pyannote[11].end 57.91221875
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 54.18284375
transcript.pyannote[12].end 54.89159375
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 56.95034375
transcript.pyannote[13].end 58.40159375
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 58.40159375
transcript.pyannote[14].end 66.02909375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 66.31596875
transcript.pyannote[15].end 71.22659375
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 75.29346875
transcript.pyannote[16].end 76.05284375
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 76.96409375
transcript.pyannote[17].end 78.55034375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 78.82034375
transcript.pyannote[18].end 89.58659375
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 79.56284375
transcript.pyannote[19].end 80.98034375
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 83.68034375
transcript.pyannote[20].end 86.81909375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 90.27846875
transcript.pyannote[21].end 99.96471875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 90.37971875
transcript.pyannote[22].end 90.98721875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 98.86784375
transcript.pyannote[23].end 99.34034375
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 99.79596875
transcript.pyannote[24].end 99.94784375
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 99.96471875
transcript.pyannote[25].end 100.06596875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 100.06596875
transcript.pyannote[26].end 100.08284375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 100.26846875
transcript.pyannote[27].end 111.13596875
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 111.86159375
transcript.pyannote[28].end 113.81909375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 114.20721875
transcript.pyannote[29].end 125.44596875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 127.25159375
transcript.pyannote[30].end 129.71534375
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 131.82471875
transcript.pyannote[31].end 134.96346875
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 134.96346875
transcript.pyannote[32].end 135.33471875
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 134.98034375
transcript.pyannote[33].end 135.01409375
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 135.33471875
transcript.pyannote[34].end 137.68034375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 139.97534375
transcript.pyannote[35].end 143.19846875
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 143.48534375
transcript.pyannote[36].end 145.76346875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 146.33721875
transcript.pyannote[37].end 149.47596875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 149.98221875
transcript.pyannote[38].end 150.43784375
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 150.64034375
transcript.pyannote[39].end 152.42909375
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 152.86784375
transcript.pyannote[40].end 154.08284375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 154.33596875
transcript.pyannote[41].end 161.81159375
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 156.14159375
transcript.pyannote[42].end 156.61409375
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 157.44096875
transcript.pyannote[43].end 158.09909375
transcript.pyannote[44].speaker SPEAKER_01
transcript.pyannote[44].start 159.63471875
transcript.pyannote[44].end 166.16534375
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 162.79034375
transcript.pyannote[45].end 163.22909375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 163.70159375
transcript.pyannote[46].end 164.66346875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 166.16534375
transcript.pyannote[47].end 180.88034375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 166.19909375
transcript.pyannote[48].end 166.90784375
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 168.10596875
transcript.pyannote[49].end 168.86534375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 169.54034375
transcript.pyannote[50].end 169.77659375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 182.28096875
transcript.pyannote[51].end 192.33846875
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 192.54096875
transcript.pyannote[52].end 192.82784375
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 192.77721875
transcript.pyannote[53].end 194.22846875
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 194.04284375
transcript.pyannote[54].end 198.29534375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 197.95784375
transcript.pyannote[55].end 199.81409375
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 199.32471875
transcript.pyannote[56].end 210.36096875
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 210.47909375
transcript.pyannote[57].end 212.82471875
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 212.58846875
transcript.pyannote[58].end 222.94971875
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 217.26284375
transcript.pyannote[59].end 217.41471875
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 221.16096875
transcript.pyannote[60].end 233.96909375
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 223.55721875
transcript.pyannote[61].end 224.40096875
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 230.45909375
transcript.pyannote[62].end 230.76284375
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 233.61471875
transcript.pyannote[63].end 244.16159375
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 241.03971875
transcript.pyannote[64].end 241.71471875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 243.85784375
transcript.pyannote[65].end 247.58721875
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 245.96721875
transcript.pyannote[66].end 249.56159375
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 248.22846875
transcript.pyannote[67].end 248.38034375
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 249.54471875
transcript.pyannote[68].end 251.19846875
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 250.57409375
transcript.pyannote[69].end 277.99596875
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 253.22346875
transcript.pyannote[70].end 256.00784375
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 256.61534375
transcript.pyannote[71].end 257.30721875
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 264.14159375
transcript.pyannote[72].end 264.42846875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 265.86284375
transcript.pyannote[73].end 266.06534375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 273.77721875
transcript.pyannote[74].end 274.14846875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 277.42221875
transcript.pyannote[75].end 283.88534375
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 282.77159375
transcript.pyannote[76].end 295.25909375
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 294.41534375
transcript.pyannote[77].end 297.73971875
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 295.36034375
transcript.pyannote[78].end 304.10159375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 303.96659375
transcript.pyannote[79].end 304.59096875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 304.27034375
transcript.pyannote[80].end 319.06971875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 306.22784375
transcript.pyannote[81].end 306.48096875
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 318.54659375
transcript.pyannote[82].end 319.67721875
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 319.67721875
transcript.pyannote[83].end 345.34409375
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 345.93471875
transcript.pyannote[84].end 366.45471875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 363.24846875
transcript.pyannote[85].end 363.50159375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 366.45471875
transcript.pyannote[86].end 377.13659375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 377.38971875
transcript.pyannote[87].end 385.77659375
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 378.18284375
transcript.pyannote[88].end 378.79034375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 379.48221875
transcript.pyannote[89].end 379.66784375
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 386.24909375
transcript.pyannote[90].end 387.22784375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 387.78471875
transcript.pyannote[91].end 388.34159375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 388.78034375
transcript.pyannote[92].end 390.70409375
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 390.72096875
transcript.pyannote[93].end 395.93534375
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 394.88909375
transcript.pyannote[94].end 398.56784375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 396.28971875
transcript.pyannote[95].end 398.24721875
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 398.39909375
transcript.pyannote[96].end 402.68534375
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 402.02721875
transcript.pyannote[97].end 404.82846875
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 404.44034375
transcript.pyannote[98].end 404.71034375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 404.81159375
transcript.pyannote[99].end 413.02971875
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 413.85659375
transcript.pyannote[100].end 420.82596875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 416.69159375
transcript.pyannote[101].end 416.70846875
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 416.79284375
transcript.pyannote[102].end 417.07971875
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 421.46721875
transcript.pyannote[103].end 483.11159375
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 483.92159375
transcript.pyannote[104].end 494.46846875
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 495.63284375
transcript.pyannote[105].end 497.15159375
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 497.87721875
transcript.pyannote[106].end 503.05784375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 503.19284375
transcript.pyannote[107].end 504.12096875
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 503.41221875
transcript.pyannote[108].end 503.58096875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 504.50909375
transcript.pyannote[109].end 504.79596875
transcript.pyannote[110].speaker SPEAKER_01
transcript.pyannote[110].start 505.21784375
transcript.pyannote[110].end 508.13721875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 508.18784375
transcript.pyannote[111].end 512.99721875
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 510.97221875
transcript.pyannote[112].end 512.91284375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 513.31784375
transcript.pyannote[113].end 520.72596875
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 521.13096875
transcript.pyannote[114].end 521.63721875
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 521.89034375
transcript.pyannote[115].end 523.96596875
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 524.11784375
transcript.pyannote[116].end 533.85471875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 534.17534375
transcript.pyannote[117].end 535.39034375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 535.72784375
transcript.pyannote[118].end 538.17471875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 538.47846875
transcript.pyannote[119].end 540.95909375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 541.31346875
transcript.pyannote[120].end 541.97159375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 542.35971875
transcript.pyannote[121].end 544.94159375
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 544.97534375
transcript.pyannote[122].end 545.02596875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 545.21159375
transcript.pyannote[123].end 548.02971875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 548.21534375
transcript.pyannote[124].end 549.81846875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 550.20659375
transcript.pyannote[125].end 550.72971875
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 551.10096875
transcript.pyannote[126].end 552.55221875
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 552.65346875
transcript.pyannote[127].end 553.37909375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 553.64909375
transcript.pyannote[128].end 557.37846875
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 557.91846875
transcript.pyannote[129].end 563.41971875
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 559.77471875
transcript.pyannote[130].end 560.04471875
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 560.44971875
transcript.pyannote[131].end 561.56346875
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 563.41971875
transcript.pyannote[132].end 591.07784375
transcript.pyannote[133].speaker SPEAKER_00
transcript.pyannote[133].start 591.26346875
transcript.pyannote[133].end 614.65221875
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 616.35659375
transcript.pyannote[134].end 631.02096875
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 631.08846875
transcript.pyannote[135].end 634.61534375
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 634.61534375
transcript.pyannote[136].end 638.14221875
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 635.74596875
transcript.pyannote[137].end 642.88409375
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 643.13721875
transcript.pyannote[138].end 643.42409375
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 643.62659375
transcript.pyannote[139].end 647.18721875
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 647.55846875
transcript.pyannote[140].end 655.62471875
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 656.13096875
transcript.pyannote[141].end 656.97471875
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 657.16034375
transcript.pyannote[142].end 660.45096875
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 660.88971875
transcript.pyannote[143].end 677.52846875
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 666.62721875
transcript.pyannote[144].end 667.67346875
transcript.pyannote[145].speaker SPEAKER_00
transcript.pyannote[145].start 670.72784375
transcript.pyannote[145].end 671.04846875
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 671.09909375
transcript.pyannote[146].end 671.13284375
transcript.pyannote[147].speaker SPEAKER_00
transcript.pyannote[147].start 676.97159375
transcript.pyannote[147].end 681.64596875
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 679.80659375
transcript.pyannote[148].end 690.48846875
transcript.pyannote[149].speaker SPEAKER_00
transcript.pyannote[149].start 684.91971875
transcript.pyannote[149].end 685.20659375
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 685.76346875
transcript.pyannote[150].end 686.32034375
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 689.34096875
transcript.pyannote[151].end 695.04471875
transcript.pyannote[152].speaker SPEAKER_00
transcript.pyannote[152].start 695.50034375
transcript.pyannote[152].end 701.08596875
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 695.55096875
transcript.pyannote[153].end 696.29346875
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 697.37346875
transcript.pyannote[154].end 697.49159375
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 698.23409375
transcript.pyannote[155].end 705.37221875
transcript.pyannote[156].speaker SPEAKER_01
transcript.pyannote[156].start 705.57471875
transcript.pyannote[156].end 708.46034375
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 708.83159375
transcript.pyannote[157].end 710.48534375
transcript.pyannote[158].speaker SPEAKER_00
transcript.pyannote[158].start 710.48534375
transcript.pyannote[158].end 710.94096875
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 710.51909375
transcript.pyannote[159].end 710.55284375
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 710.56971875
transcript.pyannote[160].end 716.34096875
transcript.pyannote[161].speaker SPEAKER_00
transcript.pyannote[161].start 712.71284375
transcript.pyannote[161].end 712.99971875
transcript.pyannote[162].speaker SPEAKER_00
transcript.pyannote[162].start 715.12596875
transcript.pyannote[162].end 715.78409375
transcript.pyannote[163].speaker SPEAKER_00
transcript.pyannote[163].start 715.85159375
transcript.pyannote[163].end 721.30221875
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 716.54346875
transcript.pyannote[164].end 718.36596875
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 718.87221875
transcript.pyannote[165].end 721.06596875
transcript.pyannote[166].speaker SPEAKER_01
transcript.pyannote[166].start 721.30221875
transcript.pyannote[166].end 727.71471875
transcript.pyannote[167].speaker SPEAKER_00
transcript.pyannote[167].start 725.06534375
transcript.pyannote[167].end 725.63909375
transcript.pyannote[168].speaker SPEAKER_00
transcript.pyannote[168].start 725.99346875
transcript.pyannote[168].end 726.38159375
transcript.pyannote[169].speaker SPEAKER_00
transcript.pyannote[169].start 727.71471875
transcript.pyannote[169].end 752.40284375
transcript.pyannote[170].speaker SPEAKER_00
transcript.pyannote[170].start 753.16221875
transcript.pyannote[170].end 756.13221875
transcript.pyannote[171].speaker SPEAKER_01
transcript.pyannote[171].start 753.28034375
transcript.pyannote[171].end 760.70534375
transcript.pyannote[172].speaker SPEAKER_00
transcript.pyannote[172].start 758.39346875
transcript.pyannote[172].end 758.66346875
transcript.pyannote[173].speaker SPEAKER_01
transcript.pyannote[173].start 760.92471875
transcript.pyannote[173].end 766.49346875
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 763.65846875
transcript.pyannote[174].end 764.62034375
transcript.pyannote[175].speaker SPEAKER_00
transcript.pyannote[175].start 766.78034375
transcript.pyannote[175].end 792.49784375
transcript.pyannote[176].speaker SPEAKER_00
transcript.pyannote[176].start 792.85221875
transcript.pyannote[176].end 797.32409375
transcript.pyannote[177].speaker SPEAKER_00
transcript.pyannote[177].start 797.71221875
transcript.pyannote[177].end 798.30284375
transcript.pyannote[178].speaker SPEAKER_01
transcript.pyannote[178].start 797.72909375
transcript.pyannote[178].end 798.42096875
transcript.pyannote[179].speaker SPEAKER_00
transcript.pyannote[179].start 799.16346875
transcript.pyannote[179].end 803.53409375
transcript.pyannote[180].speaker SPEAKER_01
transcript.pyannote[180].start 802.90971875
transcript.pyannote[180].end 803.85471875
transcript.pyannote[181].speaker SPEAKER_00
transcript.pyannote[181].start 803.77034375
transcript.pyannote[181].end 803.78721875
transcript.pyannote[182].speaker SPEAKER_00
transcript.pyannote[182].start 803.80409375
transcript.pyannote[182].end 804.46221875
transcript.pyannote[183].speaker SPEAKER_01
transcript.pyannote[183].start 804.37784375
transcript.pyannote[183].end 804.90096875
transcript.pyannote[184].speaker SPEAKER_00
transcript.pyannote[184].start 804.74909375
transcript.pyannote[184].end 804.76596875
transcript.pyannote[185].speaker SPEAKER_00
transcript.pyannote[185].start 804.79971875
transcript.pyannote[185].end 807.98909375
transcript.pyannote[186].speaker SPEAKER_01
transcript.pyannote[186].start 804.96846875
transcript.pyannote[186].end 805.66034375
transcript.pyannote[187].speaker SPEAKER_01
transcript.pyannote[187].start 805.96409375
transcript.pyannote[187].end 806.40284375
transcript.pyannote[188].speaker SPEAKER_00
transcript.pyannote[188].start 808.41096875
transcript.pyannote[188].end 810.60471875
transcript.pyannote[189].speaker SPEAKER_00
transcript.pyannote[189].start 811.31346875
transcript.pyannote[189].end 815.70096875
transcript.pyannote[190].speaker SPEAKER_01
transcript.pyannote[190].start 812.96721875
transcript.pyannote[190].end 813.50721875
transcript.pyannote[191].speaker SPEAKER_01
transcript.pyannote[191].start 814.75596875
transcript.pyannote[191].end 821.28659375
transcript.pyannote[192].speaker SPEAKER_00
transcript.pyannote[192].start 815.71784375
transcript.pyannote[192].end 816.02159375
transcript.pyannote[193].speaker SPEAKER_00
transcript.pyannote[193].start 817.03409375
transcript.pyannote[193].end 829.20096875
transcript.pyannote[194].speaker SPEAKER_00
transcript.pyannote[194].start 829.74096875
transcript.pyannote[194].end 849.13034375
transcript.pyannote[195].speaker SPEAKER_01
transcript.pyannote[195].start 833.23409375
transcript.pyannote[195].end 837.79034375
transcript.pyannote[196].speaker SPEAKER_01
transcript.pyannote[196].start 838.78596875
transcript.pyannote[196].end 839.14034375
transcript.pyannote[197].speaker SPEAKER_01
transcript.pyannote[197].start 841.26659375
transcript.pyannote[197].end 841.58721875
transcript.pyannote[198].speaker SPEAKER_01
transcript.pyannote[198].start 846.61596875
transcript.pyannote[198].end 846.73409375
transcript.pyannote[199].speaker SPEAKER_01
transcript.pyannote[199].start 846.80159375
transcript.pyannote[199].end 846.98721875
transcript.pyannote[200].speaker SPEAKER_01
transcript.pyannote[200].start 848.64096875
transcript.pyannote[200].end 849.53534375
transcript.pyannote[201].speaker SPEAKER_00
transcript.pyannote[201].start 849.67034375
transcript.pyannote[201].end 852.10034375
transcript.pyannote[202].speaker SPEAKER_01
transcript.pyannote[202].start 852.28596875
transcript.pyannote[202].end 858.59721875
transcript.pyannote[203].speaker SPEAKER_00
transcript.pyannote[203].start 853.70346875
transcript.pyannote[203].end 854.73284375
transcript.pyannote[204].speaker SPEAKER_00
transcript.pyannote[204].start 855.55971875
transcript.pyannote[204].end 857.82096875
transcript.whisperx[0].start 7.423
transcript.whisperx[0].end 12.588
transcript.whisperx[0].text 謝謝昭偉 有請張秋元富人市長富人市長您好我想請問您過去幾年內軍公教調薪的次數跟幅度是多少您可以簡單告訴我們嗎過去十年內好了
transcript.whisperx[1].start 34.882
transcript.whisperx[1].end 38.963
transcript.whisperx[1].text 過去十年內我們從107條3%111條4%113條4%114條3%那如果累進的話應該是名目上是14%累進的話應該會到14.7%
transcript.whisperx[2].start 53.318
transcript.whisperx[2].end 60.944
transcript.whisperx[2].text 14.7%是過去這樣算是十年內嗎?對,對,十年內那因為這個是民進黨執政的這幾年內嘛調了14.7%照這樣講對不對那之前馬總統執政那八年調了幾%可以告訴大家嗎?就是只有100年之後調過3%
transcript.whisperx[3].start 78.948
transcript.whisperx[3].end 85.035
transcript.whisperx[3].text 所以只有調過3%是一次 對那我想你講話這個都要有數據啦就馬總統執政那8年就是為軍公教是公教還是軍公教
transcript.whisperx[4].start 90.519
transcript.whisperx[4].end 110.684
transcript.whisperx[4].text 軍公教軍公教就是3%的調薪那民進黨執政的這10年調了14點幾%這樣講沒錯吧是所以我想其實民進黨政府過去大家都好像覺得他對軍公教不好可是從調薪這件事情上是非常的正面這樣沒錯吧我們其實是積極在處理
transcript.whisperx[5].start 114.261
transcript.whisperx[5].end 133.668
transcript.whisperx[5].text 好有積極在處理那肯定你們那可以依照目前的做法對不對就是是誰在決定有哪些機制有誰參與可以告訴大家嗎目前就是有我們有一個這個待遇調整的這個審議委員會那他的這個
transcript.whisperx[6].start 140.014
transcript.whisperx[6].end 153.628
transcript.whisperx[6].text 就是他的成員包括軍公教的主管 軍公教勞工的主管還有國發會還有財主然後還有地方政府然後還有學者專家
transcript.whisperx[7].start 154.42
transcript.whisperx[7].end 180.407
transcript.whisperx[7].text 所以目前有學者專家 有地方政府代表然後有軍公教的這些單位的主管機關譬如說國防部、全區部、教育部然後也有學者專家幾人所以其實目前有一個機制那您覺得這是我們看到這個設置要點的您覺得現行的審議委員會的組成到底代表性足不足夠
transcript.whisperx[8].start 182.318
transcript.whisperx[8].end 210.075
transcript.whisperx[8].text 我們現在在推法治化的過程裡面我們是我們也認為可以把這個公教團體的代表基層代表可以納進來委員會裡面所以你們支持可以納入軍公教的基層代表我們是朝這個方向來處理因為目前比較是主管機關譬如說國防部教育部這是主管機關那比較沒有就是基層的代表所以你們同意對不對
transcript.whisperx[9].start 210.695
transcript.whisperx[9].end 234.643
transcript.whisperx[9].text 我們的草案是往這個方向規劃的確是教育部代表跟教師代表基層教師公會的意見很可能是有衝突的向蔣沒錯所以我其實也肯定你們教育部還是教育部如果以我以前在教育部服務我們在教育現場其實是一體的所以我們會都希望整個領域好了解啦
transcript.whisperx[10].start 235.003
transcript.whisperx[10].end 255.191
transcript.whisperx[10].text 那但是因為我們長期在監督教育部然後也為教師爭取薪資的提升因為全球其實教師都遇到這個問題教育部如果比較難過的時候應該是資源的爭取的時候因為教育部他畢竟要尊重你們人種的意見我們人種其實也很努力所以我也幫教育部跟你們人種爭取我們教師要有增加平衡因為現在的年輕世代跟數位時代
transcript.whisperx[11].start 258.792
transcript.whisperx[11].end 282.697
transcript.whisperx[11].text 真的比較難就是大家的青少年主體性越來越高教師的負擔真的增高了所以薪水增加跟人數要增加這個部分都是我們爭取的所以我們知道教育部相對來講他必須要體恤你們的看法有有 上次委員詢問的我們美德光跟教育部一起處理其實我們原本對他們學校是沒有
transcript.whisperx[12].start 283.177
transcript.whisperx[12].end 297.351
transcript.whisperx[12].text 那我想合理來講的話就是不管是立委或者是基層教師公會當然可以就是爭取就是基層公務員跟教師的權益更大聲啦這樣講沒錯所以我其實是要肯定你們啦我看你們的工商時報人總有講到會議要納入基層代表是
transcript.whisperx[13].start 304.498
transcript.whisperx[13].end 319.601
transcript.whisperx[13].text 我覺得這是一個很好的表示雖然民進黨執政這些年為軍公教調薪14點多趴遠高於前面的國民黨執政那8年但是我覺得就是都是可以越改善越好的我們希望越來越好
transcript.whisperx[14].start 320.001
transcript.whisperx[14].end 345.119
transcript.whisperx[14].text 那所以肯定人總回應就是說會議將納入基層代表那我現在想要請你們專業表達意見納入基層代表到底是怎麼個納入法我研究了一下民眾黨團的版本跟我們翁小玲召委的版本這裡面都有民眾黨版本是公務人員代表一人教師代表一人可是沒有軍人代表
transcript.whisperx[15].start 345.987
transcript.whisperx[15].end 366.136
transcript.whisperx[15].text 那翁曉琳委員的版本是人數更多因為他是25人民眾黨版19人所以他是三個公務員代表三個教師代表軍人代表三人那您覺得應該要怎麼樣納入基層的方式更理想呢因為剛剛聽起來您覺得軍人不適合放在裡面嗎
transcript.whisperx[16].start 366.656
transcript.whisperx[16].end 390.576
transcript.whisperx[16].text 我們目前的意見是這樣因為我們也看了其他國家因為軍人他的身份特性比較特別他是保衛國家的有一個比較高強度我們當然軍人聲譽也要放在裡面所以現在目前是規劃國防部來代表以過去的調心軍人我們絕對會優先去考量他
transcript.whisperx[17].start 391.236
transcript.whisperx[17].end 412.596
transcript.whisperx[17].text 對 以我們看到的是這樣子就是絕對不會也不能夠就是不管朝野其實對這一塊其實都很關心所以你們認為軍人是分開處理比較好對 我們讓國防部來代表軍人那就人數上民眾黨版這個是各一人翁小林委員的版本各三人您有沒有覺得哪一種比較好
transcript.whisperx[18].start 414.111
transcript.whisperx[18].end 440.252
transcript.whisperx[18].text 我想我們尊重各委員的提案到時候勤政院版進來以後可以大家一起討論了解 因為我們的了解就是教師代表其實就好幾個不同的工會 不同的團體那這部分你們有正在研商中那我想請問你 因為剛剛講的是那個委員會那薪資調整的依據就是民眾黨版的沒有寫
transcript.whisperx[19].start 441.133
transcript.whisperx[19].end 459.29
transcript.whisperx[19].text 他是說要參考這些勞動生產力勞工平均薪資國家經濟狀況然後等等然後可是翁曉琳委員的版本比較有一點相對比較硬性的指標譬如飄增比率不得低於消費者物價指數累積成長率之二分之一我是覺得
transcript.whisperx[20].start 460.411
transcript.whisperx[20].end 482.914
transcript.whisperx[20].text 還好啦可能還有人覺得就是說這樣到底足不足夠那他有提到消費者物價指數打3%的時候一定要給予調整那我請助理幫我找出最低工資法因為我們有一個最低工資法是有一個機制的來做一個比較那依照人種的專業界見解你覺得怎麼樣的做法更妥適呢
transcript.whisperx[21].start 483.996
transcript.whisperx[21].end 512.289
transcript.whisperx[21].text 就這個指數的部分怎麼個條法應該怎麼參考是翁曉琳委員辦還是民眾黨辦還是最低工資法這邊參酌的這個指數跟委員報告其實目前在台灣我們參考的指數這個範圍是大的當然是在台灣我們大概會比較聚焦在消費者的物價指數的就是實質購買力的部分比較受
transcript.whisperx[22].start 513.45
transcript.whisperx[22].end 533.211
transcript.whisperx[22].text 比較受到一些討論關注我們也參考了GDP經濟成長率也會參考美人的平均國民所得然後也會民間企業的薪資水準然後還有我們的財政狀況做一個綜合性的考量那我覺得這個
transcript.whisperx[23].start 534.272
transcript.whisperx[23].end 562.853
transcript.whisperx[23].text 指標的部分因為各國的指標也不太一樣譬如說剛剛張艾亞林委員其實也有提就是在日本其實他是用民間薪資因為日本大概跟民間的對接是比較密的然後在台灣其實我們過去的討論都一直會比較專注在實質購買率上面其實這些指標其實都有可能是好的指標我們院板進來以後大家一起來
transcript.whisperx[24].start 563.493
transcript.whisperx[24].end 589.816
transcript.whisperx[24].text 那我想看起來你們還就是這部分有你們的想法但是目前還沒辦法揭露那另外有一個關鍵的部分也想請問您因為到底這個審議委員會說了算還是行政院有沒有一個商議權民眾黨團的版本我看到的是還有一個最後最終決定是立法院審查那如果行政院不核定的時候他又是再回去開審議會
transcript.whisperx[25].start 591.417
transcript.whisperx[25].end 612.826
transcript.whisperx[25].text 那國民黨團的翁曉林委員的版本是行政院不得調整變更除非國家有財政重大困難那這部分差異很大因為民眾黨團的版本還要來立法院最後審查那翁曉林委員的版本幾乎是這個審議委員會說了算那您認為應該要怎麼處理比較好
transcript.whisperx[26].start 616.597
transcript.whisperx[26].end 629.574
transcript.whisperx[26].text 跟委員報告我們都尊重各委員的提案那在院版的部分我早上提了也收集了很多其他國家的做法像美日韓這幾個在國際上比較被討論的國家
transcript.whisperx[27].start 634.961
transcript.whisperx[27].end 651.034
transcript.whisperx[27].text 美日韓其實都是有一個專者的機構他會負責這些相關的指標的一些這個收集跟評估然後在提出之前也會讓這個公教團體有他表達意見的機會那最後在
transcript.whisperx[28].start 657.278
transcript.whisperx[28].end 676.186
transcript.whisperx[28].text 但是最後的這個決策權因為主政的部門其實他本來就是受全民的附託他必須要對國家總資源的分配他必須要負責這個責任所以現在先進國家也都是到最後必須要由主政者去做
transcript.whisperx[29].start 676.966
transcript.whisperx[29].end 686.073
transcript.whisperx[29].text 所以你說先進民主國家是會尤其是政治負責像美國有時候條新的監議也會請總統去決定日本也會給國會跟內閣去做監議有些國家是給行政權決定有些國家是國會跟內閣是這樣嗎
transcript.whisperx[30].start 695.861
transcript.whisperx[30].end 714.19
transcript.whisperx[30].text 因為內閣制的內閣就是國會我們國家其實也會到國會只是這個階段不同就是在這個決策要不要調新之前是在行政院做決定行政院決定以後他就必須要並總預算編入總預算送到國會來
transcript.whisperx[31].start 717.092
transcript.whisperx[31].end 730.069
transcript.whisperx[31].text 那國會通過以後送給總統公佈那這樣的條件案才會生效所以其實我們也是要到國會我自己是看了覺得民眾黨團的版本會有一個迴旋
transcript.whisperx[32].start 732.472
transcript.whisperx[32].end 752.214
transcript.whisperx[32].text 因為他是說如果行政院不核定的時候再開審議會那就沒有再寫後面怎麼樣了有可能會陷入一個無止境的迴旋所以我覺得這個設計非常的重要那請問任總你們現在這個草案預計的時程是什麼因為我看到說你們已經正在送行政院的院會是不是
transcript.whisperx[33].start 754.951
transcript.whisperx[33].end 766.049
transcript.whisperx[33].text 對這個朝野委員的對這個案子的關心我們有跟行政報告行政也很慎重在討論這個那我們希望盡快送過來
transcript.whisperx[34].start 767.12
transcript.whisperx[34].end 791.883
transcript.whisperx[34].text 那我是相信行政院的版本不會虧待軍公教啦因為從你們的行為過去就是14%的薪資的漲幅那當然就是說如果能夠制度化從你們目前的行政命令進一步法治化我相信你們就是說也會謹慎考慮那我本來是要請你參著民主國家的公務員調心公式跟決策機制那您剛說你們已經在參考美日韓嗎
transcript.whisperx[35].start 792.924
transcript.whisperx[35].end 797.033
transcript.whisperx[35].text 那美日韓是不是可以至少給我們一個書面報告好嗎盡快
transcript.whisperx[36].start 799.412
transcript.whisperx[36].end 828.331
transcript.whisperx[36].text 多久之內可以給我們因為我想我們到時候委員會審議的時候一個月好不好一個月那盡快因為你們已經研究了可不可以兩個禮拜啊我擔心那個翁委員這邊會不會速審啊我是希望可以等你們行政院的版本我們是希望翁委員這邊可以等我們行政院的版本因為我看到民眾反反我是相信這個設計等一下萬一等一下進步二讀快速選會的話這個可能會造成就是無法預測的影響
transcript.whisperx[37].start 830.292
transcript.whisperx[37].end 855.418
transcript.whisperx[37].text 你們的書面資料可以給我們嗎?兩週可以嗎?早一點給我們,讓大家謹慎考慮因為我是從你們的行為相信條新的部分不會虧待軍公教那但事均說,既然要討論這個版本謹慎好好的設計非常的重要,好不好?那預計期程現在沒辦法告訴我們是不是?我們在努力,我們已經就密集在討論這個議題好,謝謝好,謝謝委員