iVOD / 164285

Field Value
IVOD_ID 164285
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/164285
日期 2025-10-16
會議資料.會議代碼 委員會-11-4-15-5
會議資料.會議代碼:str 第11屆第4會期內政委員會第5次全體委員會議
會議資料.屆 11
會議資料.會期 4
會議資料.會次 5
會議資料.種類 委員會
會議資料.委員會代碼[0] 15
會議資料.委員會代碼:str[0] 內政委員會
會議資料.標題 第11屆第4會期內政委員會第5次全體委員會議
影片種類 Clip
開始時間 2025-10-16T11:17:30+08:00
結束時間 2025-10-16T11:28:03+08:00
影片長度 00:10:33
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6022c9f6d63255a3848761666d11abbea3b07049f443442ad77ab6ef5aede8985dc74b8a2e1778a35ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 徐欣瑩
委員發言時間 11:17:30 - 11:28:03
會議時間 2025-10-16T09:00:00+08:00
會議名稱 立法院第11屆第4會期內政委員會第5次全體委員會議(事由:邀請內政部部長、海洋委員會主任委員、內政部警政署署長、內政部消防署署長就「警察、消防、海巡、移民及空中勤務總隊人員危勞津貼及退休權益之保障」進行專題報告並備質詢,另請行政院人事行政總處、行政院主計總處、銓敘部派員列席備詢。)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 6.42659375
transcript.pyannote[0].end 9.48096875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 10.67909375
transcript.pyannote[1].end 11.35409375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 16.45034375
transcript.pyannote[2].end 16.70346875
transcript.pyannote[3].speaker SPEAKER_03
transcript.pyannote[3].start 17.00721875
transcript.pyannote[3].end 17.05784375
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 17.05784375
transcript.pyannote[4].end 17.14221875
transcript.pyannote[5].speaker SPEAKER_03
transcript.pyannote[5].start 17.14221875
transcript.pyannote[5].end 17.20971875
transcript.pyannote[6].speaker SPEAKER_03
transcript.pyannote[6].start 17.58096875
transcript.pyannote[6].end 17.63159375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 17.63159375
transcript.pyannote[7].end 19.79159375
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 19.92659375
transcript.pyannote[8].end 23.25096875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 24.38159375
transcript.pyannote[9].end 25.47846875
transcript.pyannote[10].speaker SPEAKER_03
transcript.pyannote[10].start 26.18721875
transcript.pyannote[10].end 28.11096875
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 26.18721875
transcript.pyannote[11].end 28.16159375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 28.66784375
transcript.pyannote[12].end 32.09346875
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 32.78534375
transcript.pyannote[13].end 40.34534375
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 40.95284375
transcript.pyannote[14].end 44.07471875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 44.96909375
transcript.pyannote[15].end 46.92659375
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 47.16284375
transcript.pyannote[16].end 49.74471875
transcript.pyannote[17].speaker SPEAKER_03
transcript.pyannote[17].start 48.19221875
transcript.pyannote[17].end 48.96846875
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 48.96846875
transcript.pyannote[18].end 49.05284375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 49.89659375
transcript.pyannote[19].end 52.10721875
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 52.98471875
transcript.pyannote[20].end 57.94596875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 59.07659375
transcript.pyannote[21].end 59.53221875
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 59.80221875
transcript.pyannote[22].end 67.12596875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 65.64096875
transcript.pyannote[23].end 66.13034375
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 66.72096875
transcript.pyannote[24].end 69.72471875
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 69.62346875
transcript.pyannote[25].end 72.82971875
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 69.99471875
transcript.pyannote[26].end 71.69909375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 73.23471875
transcript.pyannote[27].end 74.82096875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 75.39471875
transcript.pyannote[28].end 77.68971875
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 78.41534375
transcript.pyannote[29].end 81.87471875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 83.34284375
transcript.pyannote[30].end 89.24909375
transcript.pyannote[31].speaker SPEAKER_03
transcript.pyannote[31].start 90.66659375
transcript.pyannote[31].end 98.64846875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 90.97034375
transcript.pyannote[32].end 93.78846875
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 95.64471875
transcript.pyannote[33].end 97.97346875
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 98.64846875
transcript.pyannote[34].end 104.84159375
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 105.16221875
transcript.pyannote[35].end 117.12659375
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 114.81471875
transcript.pyannote[36].end 115.50659375
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 116.02971875
transcript.pyannote[37].end 116.09721875
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 116.18159375
transcript.pyannote[38].end 116.53596875
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 116.63721875
transcript.pyannote[39].end 116.73846875
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 116.73846875
transcript.pyannote[40].end 116.75534375
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 117.56534375
transcript.pyannote[41].end 117.95346875
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 118.17284375
transcript.pyannote[42].end 121.86846875
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 122.49284375
transcript.pyannote[43].end 123.85971875
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 124.55159375
transcript.pyannote[44].end 125.71596875
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 125.83409375
transcript.pyannote[45].end 149.83034375
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 150.42096875
transcript.pyannote[46].end 151.83846875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 152.69909375
transcript.pyannote[47].end 161.32221875
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 161.87909375
transcript.pyannote[48].end 163.39784375
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 164.81534375
transcript.pyannote[49].end 173.87721875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 174.60284375
transcript.pyannote[50].end 176.05409375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 176.72909375
transcript.pyannote[51].end 179.59784375
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 180.34034375
transcript.pyannote[52].end 180.45846875
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 181.75784375
transcript.pyannote[53].end 197.41784375
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 197.68784375
transcript.pyannote[54].end 201.06284375
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 201.78846875
transcript.pyannote[55].end 202.34534375
transcript.pyannote[56].speaker SPEAKER_02
transcript.pyannote[56].start 202.81784375
transcript.pyannote[56].end 203.77971875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 204.57284375
transcript.pyannote[57].end 207.67784375
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 208.04909375
transcript.pyannote[58].end 211.55909375
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 211.57596875
transcript.pyannote[59].end 211.59284375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 211.59284375
transcript.pyannote[60].end 212.33534375
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 212.33534375
transcript.pyannote[61].end 214.56284375
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 214.95096875
transcript.pyannote[62].end 220.09784375
transcript.pyannote[63].speaker SPEAKER_02
transcript.pyannote[63].start 221.00909375
transcript.pyannote[63].end 224.33346875
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 224.38409375
transcript.pyannote[64].end 230.39159375
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 231.08346875
transcript.pyannote[65].end 234.40784375
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 234.77909375
transcript.pyannote[66].end 235.31909375
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 235.80846875
transcript.pyannote[67].end 249.03846875
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 249.37596875
transcript.pyannote[68].end 254.48909375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 254.92784375
transcript.pyannote[69].end 265.69409375
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 257.00346875
transcript.pyannote[70].end 258.85971875
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 262.62284375
transcript.pyannote[71].end 264.12471875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 264.12471875
transcript.pyannote[72].end 264.20909375
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 265.96409375
transcript.pyannote[73].end 274.87409375
transcript.pyannote[74].speaker SPEAKER_02
transcript.pyannote[74].start 275.04284375
transcript.pyannote[74].end 277.96221875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 275.29596875
transcript.pyannote[75].end 275.75159375
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 277.86096875
transcript.pyannote[76].end 277.91159375
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 277.96221875
transcript.pyannote[77].end 278.29971875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 278.24909375
transcript.pyannote[78].end 283.64909375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 284.05409375
transcript.pyannote[79].end 296.38971875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 294.04409375
transcript.pyannote[80].end 294.46596875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 296.65971875
transcript.pyannote[81].end 300.27096875
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 300.87846875
transcript.pyannote[82].end 304.97909375
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 305.53596875
transcript.pyannote[83].end 308.08409375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 308.79284375
transcript.pyannote[84].end 310.80096875
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 311.27346875
transcript.pyannote[85].end 316.42034375
transcript.pyannote[86].speaker SPEAKER_02
transcript.pyannote[86].start 316.94346875
transcript.pyannote[86].end 318.52971875
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 318.95159375
transcript.pyannote[87].end 327.59159375
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 327.89534375
transcript.pyannote[88].end 328.97534375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 329.07659375
transcript.pyannote[89].end 329.24534375
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 329.39721875
transcript.pyannote[90].end 333.27846875
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 333.44721875
transcript.pyannote[91].end 335.86034375
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 336.02909375
transcript.pyannote[92].end 339.67409375
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 339.97784375
transcript.pyannote[93].end 341.00721875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 341.24346875
transcript.pyannote[94].end 344.01096875
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 344.19659375
transcript.pyannote[95].end 350.17034375
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 350.47409375
transcript.pyannote[96].end 356.49846875
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 356.92034375
transcript.pyannote[97].end 364.54784375
transcript.pyannote[98].speaker SPEAKER_03
transcript.pyannote[98].start 361.20659375
transcript.pyannote[98].end 361.84784375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 364.66596875
transcript.pyannote[99].end 368.91846875
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 369.77909375
transcript.pyannote[100].end 380.22471875
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 380.78159375
transcript.pyannote[101].end 381.64221875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 382.11471875
transcript.pyannote[102].end 385.00034375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 385.15221875
transcript.pyannote[103].end 387.88596875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 388.39221875
transcript.pyannote[104].end 389.32034375
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 389.67471875
transcript.pyannote[105].end 399.63096875
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 392.34096875
transcript.pyannote[106].end 393.25221875
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 393.53909375
transcript.pyannote[107].end 394.16346875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 400.32284375
transcript.pyannote[108].end 419.08784375
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 417.70409375
transcript.pyannote[109].end 417.97409375
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 419.37471875
transcript.pyannote[110].end 425.77034375
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 426.56346875
transcript.pyannote[111].end 432.25034375
transcript.pyannote[112].speaker SPEAKER_03
transcript.pyannote[112].start 432.18284375
transcript.pyannote[112].end 449.00721875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 440.29971875
transcript.pyannote[113].end 441.26159375
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 443.08409375
transcript.pyannote[114].end 443.53971875
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 444.87284375
transcript.pyannote[115].end 447.04971875
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 447.75846875
transcript.pyannote[116].end 455.20034375
transcript.pyannote[117].speaker SPEAKER_03
transcript.pyannote[117].start 449.17596875
transcript.pyannote[117].end 449.39534375
transcript.pyannote[118].speaker SPEAKER_03
transcript.pyannote[118].start 454.18784375
transcript.pyannote[118].end 461.20784375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 459.73971875
transcript.pyannote[119].end 465.25784375
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 465.47721875
transcript.pyannote[120].end 476.44596875
transcript.pyannote[121].speaker SPEAKER_03
transcript.pyannote[121].start 472.56471875
transcript.pyannote[121].end 474.97784375
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 476.53034375
transcript.pyannote[122].end 481.55909375
transcript.pyannote[123].speaker SPEAKER_02
transcript.pyannote[123].start 481.93034375
transcript.pyannote[123].end 486.84096875
transcript.pyannote[124].speaker SPEAKER_02
transcript.pyannote[124].start 487.53284375
transcript.pyannote[124].end 495.71721875
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 495.95346875
transcript.pyannote[125].end 496.78034375
transcript.pyannote[126].speaker SPEAKER_02
transcript.pyannote[126].start 497.28659375
transcript.pyannote[126].end 505.25159375
transcript.pyannote[127].speaker SPEAKER_02
transcript.pyannote[127].start 505.45409375
transcript.pyannote[127].end 511.83284375
transcript.pyannote[128].speaker SPEAKER_02
transcript.pyannote[128].start 511.96784375
transcript.pyannote[128].end 516.77721875
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 517.21596875
transcript.pyannote[129].end 522.76784375
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 523.74659375
transcript.pyannote[130].end 529.02846875
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 529.41659375
transcript.pyannote[131].end 530.64846875
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 531.10409375
transcript.pyannote[132].end 532.31909375
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 532.85909375
transcript.pyannote[133].end 534.02346875
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 534.39471875
transcript.pyannote[134].end 536.67284375
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 536.80784375
transcript.pyannote[135].end 541.71846875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 542.17409375
transcript.pyannote[136].end 545.76846875
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 546.19034375
transcript.pyannote[137].end 548.19846875
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 548.70471875
transcript.pyannote[138].end 553.24409375
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 553.76721875
transcript.pyannote[139].end 554.74596875
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 553.91909375
transcript.pyannote[140].end 559.01534375
transcript.pyannote[141].speaker SPEAKER_00
transcript.pyannote[141].start 559.50471875
transcript.pyannote[141].end 578.20221875
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 563.84159375
transcript.pyannote[142].end 563.97659375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 563.99346875
transcript.pyannote[143].end 568.22909375
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 568.87034375
transcript.pyannote[144].end 570.32159375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 577.71284375
transcript.pyannote[145].end 580.42971875
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 580.36221875
transcript.pyannote[146].end 611.47971875
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 580.44659375
transcript.pyannote[147].end 580.48034375
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 580.49721875
transcript.pyannote[148].end 582.30284375
transcript.pyannote[149].speaker SPEAKER_02
transcript.pyannote[149].start 611.47971875
transcript.pyannote[149].end 613.97721875
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 613.53846875
transcript.pyannote[150].end 614.88846875
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 614.07846875
transcript.pyannote[151].end 619.88346875
transcript.pyannote[152].speaker SPEAKER_00
transcript.pyannote[152].start 620.18721875
transcript.pyannote[152].end 621.04784375
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 621.46971875
transcript.pyannote[153].end 625.06409375
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 625.48596875
transcript.pyannote[154].end 627.15659375
transcript.pyannote[155].speaker SPEAKER_00
transcript.pyannote[155].start 629.21534375
transcript.pyannote[155].end 630.37971875
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 629.67096875
transcript.pyannote[156].end 632.03346875
transcript.pyannote[157].speaker SPEAKER_00
transcript.pyannote[157].start 631.08846875
transcript.pyannote[157].end 631.86471875
transcript.whisperx[0].start 7.173
transcript.whisperx[0].end 11.194
transcript.whisperx[0].text 好 謝謝主席 本席有請劉部長請劉部長徐委員你好部長好 社會變化很快速 您認同嗎我說我們的社會氣候變遷也非常快速那社會的各種情況也是一直在變化
transcript.whisperx[1].start 32.83
transcript.whisperx[1].end 57.531
transcript.whisperx[1].text 那今天我想特别为我们的警察人员消防人员来争取首先第一个警察的负担警民比是一个指标你应该理解吧警民比那我们看了一下有一个县市一般都认为警民比比较高是六都
transcript.whisperx[2].start 59.871
transcript.whisperx[2].end 81.611
transcript.whisperx[2].text 對不對,您的認知嘛,警民比,就是一個警察要負擔多少民眾,是不是?這個密度只要是,警民比是比較高。六都的會比較高嘛,對對對。但是新竹縣啊,新竹縣一個小小的縣市,它的警民比僅次於新北,在全國第二高。
transcript.whisperx[3].start 83.413
transcript.whisperx[3].end 88.982
transcript.whisperx[3].text 所以在這種情況下部長您覺得新竹縣的警員他的負荷重不重
transcript.whisperx[4].start 90.854
transcript.whisperx[4].end 116.251
transcript.whisperx[4].text 當然 都很重啦 我相信全國的警察都很辛苦 新竹縣市都很重 因為我有拜訪過那你有拜訪過 對對對對 我每個縣民的警察局長都有拜訪過是啊 所以在這種情況下新竹縣警民比僅次於新北市勝過其他的五都我想我們的署長自動上來了所以您也擔任過新竹縣警察局局長是的 您也很清楚嘛 對 所以
transcript.whisperx[5].start 117.632
transcript.whisperx[5].end 123.623
transcript.whisperx[5].text 在這種情況下新竹縣的警察的情況啊外調的非常多
transcript.whisperx[6].start 125.119
transcript.whisperx[6].end 151.555
transcript.whisperx[6].text 因为这个负担很重所以也蛮有名新竹县警察的流动变成我们新竹县叫跳板县市警员外调还有流动率高所以缺额也多缺额也多那警民比又那么大那再来就是我们新竹县新竹县的这个平均每人每月的消费支出全国第三高
transcript.whisperx[7].start 152.765
transcript.whisperx[7].end 178.54
transcript.whisperx[7].text 所以警察負荷又重然後當地的消費又高所以他們的經濟壓力工作壓力都非常的大那在這種情況下我們就看到這種警民比這麼繁重那我今天特別要講的是警察人員這個警勤加級表警勤加級表裡面我看到我們的這個規定
transcript.whisperx[8].start 181.806
transcript.whisperx[8].end 202.351
transcript.whisperx[8].text 最後負責的第六點好像對於只有直轄市的政府可以是治安交通警察勤務的繁重程度以自籌經費來規定來對這一些知己對象加成來給予知己所以這個情況
transcript.whisperx[9].start 204.622
transcript.whisperx[9].end 219.819
transcript.whisperx[9].text 我要跟部長還有局長 署長你應該很清楚 部長很清楚這個新竹縣警察同仁他們的負擔這麼重那在整個法令裡面
transcript.whisperx[10].start 221.049
transcript.whisperx[10].end 248.623
transcript.whisperx[10].text 他没有他的这个家籍他比这个直辖市还要重所以我们县政府呢自筹自筹了9000万今年2月行文给内政部给警政署结果因为我们就是这里面只有直辖市才可以有这种可以在家籍里面有讲台北市一倍其他几个县市其他几个直辖市可以给7成
transcript.whisperx[11].start 249.463
transcript.whisperx[11].end 254.341
transcript.whisperx[11].text 那我們現在已經自籌經費了卡在這個法令是不是可以修法
transcript.whisperx[12].start 254.983
transcript.whisperx[12].end 283.368
transcript.whisperx[12].text 对包委那这个部分对于现在目前现在是六都还有其他各县市我们会全国做统一的一个处理对对我觉得要全国全国统一的处理那会因为有一些县市是还在做沟通因为这个有一些是要地方县市政府要来做支出像新竹县市愿意嘛没有所以你们你们可以定的弹性一点嘛是现在警察已经他们又辛苦然后又要给他们加急还给不了
transcript.whisperx[13].start 284.148
transcript.whisperx[13].end 299.874
transcript.whisperx[13].text 那所以新竹縣永遠缺人因為大家都要外調因為我調到直轄市我的家籍你看喔七千八千九千嘛對不對到台北市我就增加我就一萬四到高雄七成八七
transcript.whisperx[14].start 301.134
transcript.whisperx[14].end 328.736
transcript.whisperx[14].text 多五千六七千加我就有一万两千六在新竹县就七千比人家累所以这一块我们我本席也会来修我们希望我们这个院版就是说我们警政署内政部这边也可以尽快来修因为你们二月给你们的文到现在都没有再回复啦我们警察同仁时时刻刻非常的辛苦
transcript.whisperx[15].start 329.477
transcript.whisperx[15].end 356.132
transcript.whisperx[15].text 然後我們缺額又多當然我們也要感謝這個警政署能夠每年給我們一些員額讓也減輕但是再怎麼減輕你看一個新竹縣它的警民筆是僅次於新北把其他五都都沒有那麼多那又不能給它這種加擠今天願意留在新竹縣的我們真的我們給予12萬分的敬意
transcript.whisperx[16].start 356.952
transcript.whisperx[16].end 368.642
transcript.whisperx[16].text 所以這一塊我們可不可以加速來完成那本席也建議就是說這個修法可以彈性因為剛剛我一開始問部長就是說社會一直變化
transcript.whisperx[17].start 370.007
transcript.whisperx[17].end 399.227
transcript.whisperx[17].text 在修這個法這個法在訂定的時候沒有人想過新竹縣會人口增加這麼快蹦這麼快那我相信有一些其他有潛力的縣市也是如此新竹縣全國最大的鄉在新竹縣全國最大的鎮在新竹縣全國第二大的市也在新竹縣馬上要超過對竹北市馬上要超過所以很快的全國最大的鄉鎮市全部在新竹縣
transcript.whisperx[18].start 400.367
transcript.whisperx[18].end 425.538
transcript.whisperx[18].text 好 所以這個情況我們希望中央要重視那新竹縣可能首當其衝我相信其他縣市在這個各縣市長的治理之下也會快速發展所以我們希望我們的法令不合時宜的趕快修而且要能夠跟上這個社會的變化好不好 警察人員很辛苦署長或部長我們這個詢問的這個函能不能盡快回覆
transcript.whisperx[19].start 426.604
transcript.whisperx[19].end 447.225
transcript.whisperx[19].text 我們錢都籌到九千萬放在那結果我們卡在法令中央的法令是謝謝徐穩的關心我們也非常了解這個狀況我想並不是卡在新竹縣你可能也會知道因為我剛跟你講過每個縣市長我都有去拜訪過有的願意加有的不願意加所以你們的法令看怎麼調是如果說
transcript.whisperx[20].start 447.925
transcript.whisperx[20].end 467.543
transcript.whisperx[20].text 你用警民筆的话没关系有的县市不愿意你警民筆没有到也不需要不了解那我们来多跟一些县市尤其是非六度的部分来做沟通这应该跟县市长不一定那么相关为什么因为县市长会变化四年就变了我们这个法令应该要有一个
transcript.whisperx[21].start 468.283
transcript.whisperx[21].end 486.669
transcript.whisperx[21].text 就是要有一個空間啦好不好 有一個空間了解 我們來努力那很快我用後面的時間就是新竹縣既然你看最大的鄉鎮市人口快速成長所以我們的消防那個署長您可以回座
transcript.whisperx[22].start 487.589
transcript.whisperx[22].end 516.072
transcript.whisperx[22].text 部長我們的消防人力也是我們消防人力啊我時間不夠我就舉一個一個表格啊為什麼115年明年要預計分配的人數整個的補充率缺額對上預計分配人數哇新竹縣比例1.61其他都兩位數新竹縣1.61那各位數的還有高雄市不過高雄市他的
transcript.whisperx[23].start 517.573
transcript.whisperx[23].end 541.388
transcript.whisperx[23].text 這個缺額在五、六都當中是第二少的啦所以面對這個情況部長還有署長拜託正視一下好不好還有去年啊新竹縣才一位這個消防人員他這個因公殉職我們不希望看到這種情況所以我看到這個比例數字
transcript.whisperx[24].start 542.287
transcript.whisperx[24].end 558.639
transcript.whisperx[24].text 我不得不在這裡部長也請你重視好不好怎麼會我們1.61啊新竹縣這樣人口我們這邊的警消人員都很辛苦耶來麻煩 簡單跟委員報告兩個部分一個部分這個人數明年1月份
transcript.whisperx[25].start 559.8
transcript.whisperx[25].end 581.532
transcript.whisperx[25].text 新竹縣就提那麼多的我會想辦法在部長支持之下會增加沒有啦 他們要48個 拜託有那個時間的差距我們想辦法在1月份再想辦法再從缺額的部分來做一個調整這個跟縣委員跟委員報告那另外部分就是這個應該是有誤會啦因為他們提48好不好我們來處理 那逐年跟委員
transcript.whisperx[26].start 585.394
transcript.whisperx[26].end 610.015
transcript.whisperx[26].text 報告就說特考班我們現在招生可以達到1000位正期班已經增加到400位所以目前是一年期待能夠達到1400位的量當然會考考慮到有多少人考過有多少人畢業了當然這會有一個伸縮所以上一次有跟我們報告可能沒有那麼多人可能就比較打折了那當然我們會優先來考慮到有些縣市人力缺額特別大的我們優先來考慮 謝謝
transcript.whisperx[27].start 612.597
transcript.whisperx[27].end 630.767
transcript.whisperx[27].text 這個1.61太誇張了啦好不好我們的缺額這個補充率不能這樣這樣真的是太大小眼了好嗎我們來努力你一定要讓我們至少兩位數以上真的拜託部長拜託啦一定要努力謝謝