IVOD_ID |
162440 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/162440 |
日期 |
2025-06-11 |
會議資料.會議代碼 |
聯席會議-11-3-19,20-3 |
會議資料.會議代碼:str |
第11屆第3會期經濟、財政兩委員會第3次聯席會議 |
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 |
聯席會議 |
會議資料.委員會代碼[0] |
19 |
會議資料.委員會代碼[1] |
20 |
會議資料.委員會代碼:str[0] |
經濟委員會 |
會議資料.委員會代碼:str[1] |
財政委員會 |
會議資料.標題 |
第11屆第3會期經濟、財政兩委員會第3次聯席會議 |
影片種類 |
Clip |
開始時間 |
2025-06-11T11:21:26+08:00 |
結束時間 |
2025-06-11T11:33:43+08:00 |
影片長度 |
00:12:17 |
支援功能[0] |
ai-transcript |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/5b5dae1827dbf6c98ed0624e65eb5ccbb4fab53e924c0ec1643b132f871dcdd883b6116c1c0933fe5ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
謝衣鳯 |
委員發言時間 |
11:21:26 - 11:33:43 |
會議時間 |
2025-06-11T09:00:00+08:00 |
會議名稱 |
立法院第11屆第3會期經濟、財政兩委員會第3次聯席會議(事由:審查:
一、本院委員謝衣鳯等16人擬具「農業保險法第十條條文修正草案」案。
二、本院委員邱若華等21人擬具「農業保險法第二條及第十條條文修正草案」案。
三、本院台灣民眾黨黨團擬具「農業保險法第二條及第十條條文修正草案」案。(詢答)) |
transcript.pyannote[0].speaker |
SPEAKER_01 |
transcript.pyannote[0].start |
0.03096875 |
transcript.pyannote[0].end |
2.37659375 |
transcript.pyannote[1].speaker |
SPEAKER_01 |
transcript.pyannote[1].start |
9.09284375 |
transcript.pyannote[1].end |
11.13471875 |
transcript.pyannote[2].speaker |
SPEAKER_01 |
transcript.pyannote[2].start |
11.74221875 |
transcript.pyannote[2].end |
12.80534375 |
transcript.pyannote[3].speaker |
SPEAKER_00 |
transcript.pyannote[3].start |
18.47534375 |
transcript.pyannote[3].end |
18.94784375 |
transcript.pyannote[4].speaker |
SPEAKER_01 |
transcript.pyannote[4].start |
19.36971875 |
transcript.pyannote[4].end |
19.85909375 |
transcript.pyannote[5].speaker |
SPEAKER_01 |
transcript.pyannote[5].start |
20.21346875 |
transcript.pyannote[5].end |
30.82784375 |
transcript.pyannote[6].speaker |
SPEAKER_01 |
transcript.pyannote[6].start |
30.91221875 |
transcript.pyannote[6].end |
37.35846875 |
transcript.pyannote[7].speaker |
SPEAKER_00 |
transcript.pyannote[7].start |
37.35846875 |
transcript.pyannote[7].end |
37.81409375 |
transcript.pyannote[8].speaker |
SPEAKER_01 |
transcript.pyannote[8].start |
38.32034375 |
transcript.pyannote[8].end |
38.62409375 |
transcript.pyannote[9].speaker |
SPEAKER_01 |
transcript.pyannote[9].start |
39.09659375 |
transcript.pyannote[9].end |
48.78284375 |
transcript.pyannote[10].speaker |
SPEAKER_00 |
transcript.pyannote[10].start |
42.60659375 |
transcript.pyannote[10].end |
43.06221875 |
transcript.pyannote[11].speaker |
SPEAKER_01 |
transcript.pyannote[11].start |
48.93471875 |
transcript.pyannote[11].end |
50.79096875 |
transcript.pyannote[12].speaker |
SPEAKER_01 |
transcript.pyannote[12].start |
50.99346875 |
transcript.pyannote[12].end |
51.58409375 |
transcript.pyannote[13].speaker |
SPEAKER_00 |
transcript.pyannote[13].start |
51.58409375 |
transcript.pyannote[13].end |
52.00596875 |
transcript.pyannote[14].speaker |
SPEAKER_01 |
transcript.pyannote[14].start |
52.00596875 |
transcript.pyannote[14].end |
66.41721875 |
transcript.pyannote[15].speaker |
SPEAKER_01 |
transcript.pyannote[15].start |
66.75471875 |
transcript.pyannote[15].end |
85.19909375 |
transcript.pyannote[16].speaker |
SPEAKER_01 |
transcript.pyannote[16].start |
85.40159375 |
transcript.pyannote[16].end |
118.10534375 |
transcript.pyannote[17].speaker |
SPEAKER_01 |
transcript.pyannote[17].start |
118.45971875 |
transcript.pyannote[17].end |
122.08784375 |
transcript.pyannote[18].speaker |
SPEAKER_00 |
transcript.pyannote[18].start |
122.57721875 |
transcript.pyannote[18].end |
130.62659375 |
transcript.pyannote[19].speaker |
SPEAKER_00 |
transcript.pyannote[19].start |
131.14971875 |
transcript.pyannote[19].end |
131.58846875 |
transcript.pyannote[20].speaker |
SPEAKER_00 |
transcript.pyannote[20].start |
131.87534375 |
transcript.pyannote[20].end |
136.02659375 |
transcript.pyannote[21].speaker |
SPEAKER_00 |
transcript.pyannote[21].start |
136.06034375 |
transcript.pyannote[21].end |
140.04284375 |
transcript.pyannote[22].speaker |
SPEAKER_00 |
transcript.pyannote[22].start |
140.05971875 |
transcript.pyannote[22].end |
142.87784375 |
transcript.pyannote[23].speaker |
SPEAKER_00 |
transcript.pyannote[23].start |
143.01284375 |
transcript.pyannote[23].end |
143.09721875 |
transcript.pyannote[24].speaker |
SPEAKER_01 |
transcript.pyannote[24].start |
143.09721875 |
transcript.pyannote[24].end |
143.31659375 |
transcript.pyannote[25].speaker |
SPEAKER_00 |
transcript.pyannote[25].start |
143.31659375 |
transcript.pyannote[25].end |
143.35034375 |
transcript.pyannote[26].speaker |
SPEAKER_01 |
transcript.pyannote[26].start |
143.35034375 |
transcript.pyannote[26].end |
143.36721875 |
transcript.pyannote[27].speaker |
SPEAKER_00 |
transcript.pyannote[27].start |
143.75534375 |
transcript.pyannote[27].end |
145.20659375 |
transcript.pyannote[28].speaker |
SPEAKER_00 |
transcript.pyannote[28].start |
145.52721875 |
transcript.pyannote[28].end |
145.54409375 |
transcript.pyannote[29].speaker |
SPEAKER_01 |
transcript.pyannote[29].start |
145.54409375 |
transcript.pyannote[29].end |
150.87659375 |
transcript.pyannote[30].speaker |
SPEAKER_00 |
transcript.pyannote[30].start |
147.07971875 |
transcript.pyannote[30].end |
149.15534375 |
transcript.pyannote[31].speaker |
SPEAKER_00 |
transcript.pyannote[31].start |
149.59409375 |
transcript.pyannote[31].end |
161.08596875 |
transcript.pyannote[32].speaker |
SPEAKER_00 |
transcript.pyannote[32].start |
161.76096875 |
transcript.pyannote[32].end |
166.19909375 |
transcript.pyannote[33].speaker |
SPEAKER_00 |
transcript.pyannote[33].start |
166.95846875 |
transcript.pyannote[33].end |
169.75971875 |
transcript.pyannote[34].speaker |
SPEAKER_00 |
transcript.pyannote[34].start |
170.06346875 |
transcript.pyannote[34].end |
172.37534375 |
transcript.pyannote[35].speaker |
SPEAKER_00 |
transcript.pyannote[35].start |
173.13471875 |
transcript.pyannote[35].end |
183.74909375 |
transcript.pyannote[36].speaker |
SPEAKER_01 |
transcript.pyannote[36].start |
178.31534375 |
transcript.pyannote[36].end |
178.43346875 |
transcript.pyannote[37].speaker |
SPEAKER_01 |
transcript.pyannote[37].start |
178.50096875 |
transcript.pyannote[37].end |
178.60221875 |
transcript.pyannote[38].speaker |
SPEAKER_00 |
transcript.pyannote[38].start |
184.20471875 |
transcript.pyannote[38].end |
192.77721875 |
transcript.pyannote[39].speaker |
SPEAKER_00 |
transcript.pyannote[39].start |
193.04721875 |
transcript.pyannote[39].end |
194.39721875 |
transcript.pyannote[40].speaker |
SPEAKER_00 |
transcript.pyannote[40].start |
194.58284375 |
transcript.pyannote[40].end |
201.21471875 |
transcript.pyannote[41].speaker |
SPEAKER_00 |
transcript.pyannote[41].start |
201.97409375 |
transcript.pyannote[41].end |
212.99346875 |
transcript.pyannote[42].speaker |
SPEAKER_00 |
transcript.pyannote[42].start |
213.55034375 |
transcript.pyannote[42].end |
213.97221875 |
transcript.pyannote[43].speaker |
SPEAKER_00 |
transcript.pyannote[43].start |
214.41096875 |
transcript.pyannote[43].end |
227.35409375 |
transcript.pyannote[44].speaker |
SPEAKER_01 |
transcript.pyannote[44].start |
217.29659375 |
transcript.pyannote[44].end |
217.41471875 |
transcript.pyannote[45].speaker |
SPEAKER_01 |
transcript.pyannote[45].start |
226.52721875 |
transcript.pyannote[45].end |
265.08659375 |
transcript.pyannote[46].speaker |
SPEAKER_00 |
transcript.pyannote[46].start |
234.49221875 |
transcript.pyannote[46].end |
234.86346875 |
transcript.pyannote[47].speaker |
SPEAKER_00 |
transcript.pyannote[47].start |
237.90096875 |
transcript.pyannote[47].end |
238.82909375 |
transcript.pyannote[48].speaker |
SPEAKER_00 |
transcript.pyannote[48].start |
265.08659375 |
transcript.pyannote[48].end |
275.31284375 |
transcript.pyannote[49].speaker |
SPEAKER_01 |
transcript.pyannote[49].start |
274.65471875 |
transcript.pyannote[49].end |
285.79221875 |
transcript.pyannote[50].speaker |
SPEAKER_00 |
transcript.pyannote[50].start |
277.81034375 |
transcript.pyannote[50].end |
278.04659375 |
transcript.pyannote[51].speaker |
SPEAKER_00 |
transcript.pyannote[51].start |
280.91534375 |
transcript.pyannote[51].end |
280.94909375 |
transcript.pyannote[52].speaker |
SPEAKER_01 |
transcript.pyannote[52].start |
286.07909375 |
transcript.pyannote[52].end |
294.21284375 |
transcript.pyannote[53].speaker |
SPEAKER_00 |
transcript.pyannote[53].start |
294.75284375 |
transcript.pyannote[53].end |
297.63846875 |
transcript.pyannote[54].speaker |
SPEAKER_00 |
transcript.pyannote[54].start |
297.82409375 |
transcript.pyannote[54].end |
300.30471875 |
transcript.pyannote[55].speaker |
SPEAKER_00 |
transcript.pyannote[55].start |
300.74346875 |
transcript.pyannote[55].end |
306.63284375 |
transcript.pyannote[56].speaker |
SPEAKER_00 |
transcript.pyannote[56].start |
307.15596875 |
transcript.pyannote[56].end |
310.81784375 |
transcript.pyannote[57].speaker |
SPEAKER_00 |
transcript.pyannote[57].start |
310.95284375 |
transcript.pyannote[57].end |
312.16784375 |
transcript.pyannote[58].speaker |
SPEAKER_01 |
transcript.pyannote[58].start |
312.08346875 |
transcript.pyannote[58].end |
312.48846875 |
transcript.pyannote[59].speaker |
SPEAKER_00 |
transcript.pyannote[59].start |
312.31971875 |
transcript.pyannote[59].end |
316.69034375 |
transcript.pyannote[60].speaker |
SPEAKER_00 |
transcript.pyannote[60].start |
316.96034375 |
transcript.pyannote[60].end |
340.48409375 |
transcript.pyannote[61].speaker |
SPEAKER_01 |
transcript.pyannote[61].start |
323.15346875 |
transcript.pyannote[61].end |
323.17034375 |
transcript.pyannote[62].speaker |
SPEAKER_01 |
transcript.pyannote[62].start |
323.52471875 |
transcript.pyannote[62].end |
323.57534375 |
transcript.pyannote[63].speaker |
SPEAKER_01 |
transcript.pyannote[63].start |
325.21221875 |
transcript.pyannote[63].end |
325.44846875 |
transcript.pyannote[64].speaker |
SPEAKER_00 |
transcript.pyannote[64].start |
340.78784375 |
transcript.pyannote[64].end |
344.68596875 |
transcript.pyannote[65].speaker |
SPEAKER_01 |
transcript.pyannote[65].start |
342.79596875 |
transcript.pyannote[65].end |
342.82971875 |
transcript.pyannote[66].speaker |
SPEAKER_01 |
transcript.pyannote[66].start |
342.98159375 |
transcript.pyannote[66].end |
343.04909375 |
transcript.pyannote[67].speaker |
SPEAKER_00 |
transcript.pyannote[67].start |
344.98971875 |
transcript.pyannote[67].end |
357.46034375 |
transcript.pyannote[68].speaker |
SPEAKER_01 |
transcript.pyannote[68].start |
347.74034375 |
transcript.pyannote[68].end |
347.79096875 |
transcript.pyannote[69].speaker |
SPEAKER_01 |
transcript.pyannote[69].start |
357.46034375 |
transcript.pyannote[69].end |
400.62659375 |
transcript.pyannote[70].speaker |
SPEAKER_00 |
transcript.pyannote[70].start |
361.25721875 |
transcript.pyannote[70].end |
361.59471875 |
transcript.pyannote[71].speaker |
SPEAKER_00 |
transcript.pyannote[71].start |
371.87159375 |
transcript.pyannote[71].end |
372.34409375 |
transcript.pyannote[72].speaker |
SPEAKER_00 |
transcript.pyannote[72].start |
380.34284375 |
transcript.pyannote[72].end |
380.95034375 |
transcript.pyannote[73].speaker |
SPEAKER_00 |
transcript.pyannote[73].start |
387.17721875 |
transcript.pyannote[73].end |
387.32909375 |
transcript.pyannote[74].speaker |
SPEAKER_01 |
transcript.pyannote[74].start |
401.08221875 |
transcript.pyannote[74].end |
404.44034375 |
transcript.pyannote[75].speaker |
SPEAKER_00 |
transcript.pyannote[75].start |
404.81159375 |
transcript.pyannote[75].end |
407.57909375 |
transcript.pyannote[76].speaker |
SPEAKER_01 |
transcript.pyannote[76].start |
407.47784375 |
transcript.pyannote[76].end |
407.73096875 |
transcript.pyannote[77].speaker |
SPEAKER_00 |
transcript.pyannote[77].start |
407.73096875 |
transcript.pyannote[77].end |
408.47346875 |
transcript.pyannote[78].speaker |
SPEAKER_00 |
transcript.pyannote[78].start |
408.92909375 |
transcript.pyannote[78].end |
410.86971875 |
transcript.pyannote[79].speaker |
SPEAKER_00 |
transcript.pyannote[79].start |
411.39284375 |
transcript.pyannote[79].end |
412.25346875 |
transcript.pyannote[80].speaker |
SPEAKER_00 |
transcript.pyannote[80].start |
412.43909375 |
transcript.pyannote[80].end |
424.13346875 |
transcript.pyannote[81].speaker |
SPEAKER_01 |
transcript.pyannote[81].start |
416.86034375 |
transcript.pyannote[81].end |
416.97846875 |
transcript.pyannote[82].speaker |
SPEAKER_01 |
transcript.pyannote[82].start |
417.06284375 |
transcript.pyannote[82].end |
417.19784375 |
transcript.pyannote[83].speaker |
SPEAKER_01 |
transcript.pyannote[83].start |
422.34471875 |
transcript.pyannote[83].end |
422.83409375 |
transcript.pyannote[84].speaker |
SPEAKER_00 |
transcript.pyannote[84].start |
424.97721875 |
transcript.pyannote[84].end |
436.13159375 |
transcript.pyannote[85].speaker |
SPEAKER_00 |
transcript.pyannote[85].start |
436.72221875 |
transcript.pyannote[85].end |
437.81909375 |
transcript.pyannote[86].speaker |
SPEAKER_01 |
transcript.pyannote[86].start |
437.81909375 |
transcript.pyannote[86].end |
438.07221875 |
transcript.pyannote[87].speaker |
SPEAKER_00 |
transcript.pyannote[87].start |
438.07221875 |
transcript.pyannote[87].end |
440.23221875 |
transcript.pyannote[88].speaker |
SPEAKER_01 |
transcript.pyannote[88].start |
438.08909375 |
transcript.pyannote[88].end |
438.10596875 |
transcript.pyannote[89].speaker |
SPEAKER_01 |
transcript.pyannote[89].start |
440.11409375 |
transcript.pyannote[89].end |
442.79721875 |
transcript.pyannote[90].speaker |
SPEAKER_01 |
transcript.pyannote[90].start |
442.96596875 |
transcript.pyannote[90].end |
445.07534375 |
transcript.pyannote[91].speaker |
SPEAKER_01 |
transcript.pyannote[91].start |
445.19346875 |
transcript.pyannote[91].end |
456.29721875 |
transcript.pyannote[92].speaker |
SPEAKER_01 |
transcript.pyannote[92].start |
456.75284375 |
transcript.pyannote[92].end |
462.45659375 |
transcript.pyannote[93].speaker |
SPEAKER_00 |
transcript.pyannote[93].start |
459.89159375 |
transcript.pyannote[93].end |
460.65096875 |
transcript.pyannote[94].speaker |
SPEAKER_00 |
transcript.pyannote[94].start |
461.20784375 |
transcript.pyannote[94].end |
468.43034375 |
transcript.pyannote[95].speaker |
SPEAKER_01 |
transcript.pyannote[95].start |
468.41346875 |
transcript.pyannote[95].end |
468.68346875 |
transcript.pyannote[96].speaker |
SPEAKER_00 |
transcript.pyannote[96].start |
468.88596875 |
transcript.pyannote[96].end |
474.85971875 |
transcript.pyannote[97].speaker |
SPEAKER_01 |
transcript.pyannote[97].start |
471.48471875 |
transcript.pyannote[97].end |
471.82221875 |
transcript.pyannote[98].speaker |
SPEAKER_00 |
transcript.pyannote[98].start |
475.33221875 |
transcript.pyannote[98].end |
494.08034375 |
transcript.pyannote[99].speaker |
SPEAKER_01 |
transcript.pyannote[99].start |
485.38971875 |
transcript.pyannote[99].end |
485.82846875 |
transcript.pyannote[100].speaker |
SPEAKER_00 |
transcript.pyannote[100].start |
494.51909375 |
transcript.pyannote[100].end |
498.01221875 |
transcript.pyannote[101].speaker |
SPEAKER_01 |
transcript.pyannote[101].start |
498.01221875 |
transcript.pyannote[101].end |
498.53534375 |
transcript.pyannote[102].speaker |
SPEAKER_00 |
transcript.pyannote[102].start |
498.11346875 |
transcript.pyannote[102].end |
498.18096875 |
transcript.pyannote[103].speaker |
SPEAKER_00 |
transcript.pyannote[103].start |
498.28221875 |
transcript.pyannote[103].end |
509.99346875 |
transcript.pyannote[104].speaker |
SPEAKER_01 |
transcript.pyannote[104].start |
510.36471875 |
transcript.pyannote[104].end |
519.64596875 |
transcript.pyannote[105].speaker |
SPEAKER_00 |
transcript.pyannote[105].start |
519.64596875 |
transcript.pyannote[105].end |
520.03409375 |
transcript.pyannote[106].speaker |
SPEAKER_01 |
transcript.pyannote[106].start |
520.03409375 |
transcript.pyannote[106].end |
525.88971875 |
transcript.pyannote[107].speaker |
SPEAKER_00 |
transcript.pyannote[107].start |
526.42971875 |
transcript.pyannote[107].end |
527.12159375 |
transcript.pyannote[108].speaker |
SPEAKER_01 |
transcript.pyannote[108].start |
527.22284375 |
transcript.pyannote[108].end |
527.86409375 |
transcript.pyannote[109].speaker |
SPEAKER_01 |
transcript.pyannote[109].start |
528.21846875 |
transcript.pyannote[109].end |
529.36596875 |
transcript.pyannote[110].speaker |
SPEAKER_00 |
transcript.pyannote[110].start |
529.11284375 |
transcript.pyannote[110].end |
533.16284375 |
transcript.pyannote[111].speaker |
SPEAKER_01 |
transcript.pyannote[111].start |
530.02409375 |
transcript.pyannote[111].end |
531.01971875 |
transcript.pyannote[112].speaker |
SPEAKER_00 |
transcript.pyannote[112].start |
533.39909375 |
transcript.pyannote[112].end |
534.61409375 |
transcript.pyannote[113].speaker |
SPEAKER_00 |
transcript.pyannote[113].start |
534.78284375 |
transcript.pyannote[113].end |
535.00221875 |
transcript.pyannote[114].speaker |
SPEAKER_01 |
transcript.pyannote[114].start |
535.00221875 |
transcript.pyannote[114].end |
535.01909375 |
transcript.pyannote[115].speaker |
SPEAKER_00 |
transcript.pyannote[115].start |
535.01909375 |
transcript.pyannote[115].end |
536.38596875 |
transcript.pyannote[116].speaker |
SPEAKER_01 |
transcript.pyannote[116].start |
536.11596875 |
transcript.pyannote[116].end |
538.09034375 |
transcript.pyannote[117].speaker |
SPEAKER_00 |
transcript.pyannote[117].start |
537.49971875 |
transcript.pyannote[117].end |
550.00409375 |
transcript.pyannote[118].speaker |
SPEAKER_01 |
transcript.pyannote[118].start |
541.44846875 |
transcript.pyannote[118].end |
541.80284375 |
transcript.pyannote[119].speaker |
SPEAKER_01 |
transcript.pyannote[119].start |
542.88284375 |
transcript.pyannote[119].end |
543.74346875 |
transcript.pyannote[120].speaker |
SPEAKER_00 |
transcript.pyannote[120].start |
550.12221875 |
transcript.pyannote[120].end |
558.07034375 |
transcript.pyannote[121].speaker |
SPEAKER_01 |
transcript.pyannote[121].start |
550.32471875 |
transcript.pyannote[121].end |
550.35846875 |
transcript.pyannote[122].speaker |
SPEAKER_01 |
transcript.pyannote[122].start |
550.49346875 |
transcript.pyannote[122].end |
550.51034375 |
transcript.pyannote[123].speaker |
SPEAKER_01 |
transcript.pyannote[123].start |
554.64471875 |
transcript.pyannote[123].end |
564.88784375 |
transcript.pyannote[124].speaker |
SPEAKER_00 |
transcript.pyannote[124].start |
560.24721875 |
transcript.pyannote[124].end |
566.20409375 |
transcript.pyannote[125].speaker |
SPEAKER_01 |
transcript.pyannote[125].start |
566.08596875 |
transcript.pyannote[125].end |
567.75659375 |
transcript.pyannote[126].speaker |
SPEAKER_00 |
transcript.pyannote[126].start |
567.84096875 |
transcript.pyannote[126].end |
569.22471875 |
transcript.pyannote[127].speaker |
SPEAKER_00 |
transcript.pyannote[127].start |
570.10221875 |
transcript.pyannote[127].end |
571.23284375 |
transcript.pyannote[128].speaker |
SPEAKER_01 |
transcript.pyannote[128].start |
571.70534375 |
transcript.pyannote[128].end |
573.73034375 |
transcript.pyannote[129].speaker |
SPEAKER_00 |
transcript.pyannote[129].start |
572.92034375 |
transcript.pyannote[129].end |
576.12659375 |
transcript.pyannote[130].speaker |
SPEAKER_01 |
transcript.pyannote[130].start |
574.77659375 |
transcript.pyannote[130].end |
592.83284375 |
transcript.pyannote[131].speaker |
SPEAKER_00 |
transcript.pyannote[131].start |
583.50096875 |
transcript.pyannote[131].end |
583.90596875 |
transcript.pyannote[132].speaker |
SPEAKER_00 |
transcript.pyannote[132].start |
585.34034375 |
transcript.pyannote[132].end |
585.74534375 |
transcript.pyannote[133].speaker |
SPEAKER_00 |
transcript.pyannote[133].start |
586.20096875 |
transcript.pyannote[133].end |
586.47096875 |
transcript.pyannote[134].speaker |
SPEAKER_00 |
transcript.pyannote[134].start |
591.63471875 |
transcript.pyannote[134].end |
594.92534375 |
transcript.pyannote[135].speaker |
SPEAKER_00 |
transcript.pyannote[135].start |
595.24596875 |
transcript.pyannote[135].end |
610.61909375 |
transcript.pyannote[136].speaker |
SPEAKER_01 |
transcript.pyannote[136].start |
600.64596875 |
transcript.pyannote[136].end |
600.84846875 |
transcript.pyannote[137].speaker |
SPEAKER_01 |
transcript.pyannote[137].start |
600.88221875 |
transcript.pyannote[137].end |
601.10159375 |
transcript.pyannote[138].speaker |
SPEAKER_01 |
transcript.pyannote[138].start |
610.50096875 |
transcript.pyannote[138].end |
610.85534375 |
transcript.pyannote[139].speaker |
SPEAKER_00 |
transcript.pyannote[139].start |
610.75409375 |
transcript.pyannote[139].end |
612.86346875 |
transcript.pyannote[140].speaker |
SPEAKER_00 |
transcript.pyannote[140].start |
613.38659375 |
transcript.pyannote[140].end |
618.76971875 |
transcript.pyannote[141].speaker |
SPEAKER_00 |
transcript.pyannote[141].start |
619.00596875 |
transcript.pyannote[141].end |
620.13659375 |
transcript.pyannote[142].speaker |
SPEAKER_01 |
transcript.pyannote[142].start |
619.14096875 |
transcript.pyannote[142].end |
623.71409375 |
transcript.pyannote[143].speaker |
SPEAKER_00 |
transcript.pyannote[143].start |
620.54159375 |
transcript.pyannote[143].end |
620.96346875 |
transcript.pyannote[144].speaker |
SPEAKER_00 |
transcript.pyannote[144].start |
624.00096875 |
transcript.pyannote[144].end |
632.69159375 |
transcript.pyannote[145].speaker |
SPEAKER_00 |
transcript.pyannote[145].start |
633.33284375 |
transcript.pyannote[145].end |
635.02034375 |
transcript.pyannote[146].speaker |
SPEAKER_01 |
transcript.pyannote[146].start |
635.00346875 |
transcript.pyannote[146].end |
644.16659375 |
transcript.pyannote[147].speaker |
SPEAKER_00 |
transcript.pyannote[147].start |
637.51784375 |
transcript.pyannote[147].end |
638.88471875 |
transcript.pyannote[148].speaker |
SPEAKER_00 |
transcript.pyannote[148].start |
643.17096875 |
transcript.pyannote[148].end |
646.78221875 |
transcript.pyannote[149].speaker |
SPEAKER_01 |
transcript.pyannote[149].start |
646.64721875 |
transcript.pyannote[149].end |
647.00159375 |
transcript.pyannote[150].speaker |
SPEAKER_01 |
transcript.pyannote[150].start |
647.25471875 |
transcript.pyannote[150].end |
647.59221875 |
transcript.pyannote[151].speaker |
SPEAKER_01 |
transcript.pyannote[151].start |
648.48659375 |
transcript.pyannote[151].end |
651.82784375 |
transcript.pyannote[152].speaker |
SPEAKER_00 |
transcript.pyannote[152].start |
652.31721875 |
transcript.pyannote[152].end |
652.82346875 |
transcript.pyannote[153].speaker |
SPEAKER_00 |
transcript.pyannote[153].start |
653.43096875 |
transcript.pyannote[153].end |
656.53596875 |
transcript.pyannote[154].speaker |
SPEAKER_00 |
transcript.pyannote[154].start |
656.72159375 |
transcript.pyannote[154].end |
657.19409375 |
transcript.pyannote[155].speaker |
SPEAKER_00 |
transcript.pyannote[155].start |
657.81846875 |
transcript.pyannote[155].end |
663.53909375 |
transcript.pyannote[156].speaker |
SPEAKER_00 |
transcript.pyannote[156].start |
663.57284375 |
transcript.pyannote[156].end |
663.62346875 |
transcript.pyannote[157].speaker |
SPEAKER_00 |
transcript.pyannote[157].start |
663.72471875 |
transcript.pyannote[157].end |
674.08596875 |
transcript.pyannote[158].speaker |
SPEAKER_01 |
transcript.pyannote[158].start |
668.61846875 |
transcript.pyannote[158].end |
668.63534375 |
transcript.pyannote[159].speaker |
SPEAKER_01 |
transcript.pyannote[159].start |
668.93909375 |
transcript.pyannote[159].end |
669.05721875 |
transcript.pyannote[160].speaker |
SPEAKER_01 |
transcript.pyannote[160].start |
672.44909375 |
transcript.pyannote[160].end |
676.83659375 |
transcript.pyannote[161].speaker |
SPEAKER_00 |
transcript.pyannote[161].start |
676.83659375 |
transcript.pyannote[161].end |
688.41284375 |
transcript.pyannote[162].speaker |
SPEAKER_01 |
transcript.pyannote[162].start |
684.22784375 |
transcript.pyannote[162].end |
684.29534375 |
transcript.pyannote[163].speaker |
SPEAKER_01 |
transcript.pyannote[163].start |
687.09659375 |
transcript.pyannote[163].end |
687.16409375 |
transcript.pyannote[164].speaker |
SPEAKER_00 |
transcript.pyannote[164].start |
688.64909375 |
transcript.pyannote[164].end |
689.88096875 |
transcript.pyannote[165].speaker |
SPEAKER_00 |
transcript.pyannote[165].start |
690.11721875 |
transcript.pyannote[165].end |
695.88846875 |
transcript.pyannote[166].speaker |
SPEAKER_01 |
transcript.pyannote[166].start |
696.10784375 |
transcript.pyannote[166].end |
697.79534375 |
transcript.pyannote[167].speaker |
SPEAKER_00 |
transcript.pyannote[167].start |
699.48284375 |
transcript.pyannote[167].end |
702.03096875 |
transcript.pyannote[168].speaker |
SPEAKER_01 |
transcript.pyannote[168].start |
702.08159375 |
transcript.pyannote[168].end |
702.85784375 |
transcript.pyannote[169].speaker |
SPEAKER_00 |
transcript.pyannote[169].start |
703.51596875 |
transcript.pyannote[169].end |
704.35971875 |
transcript.pyannote[170].speaker |
SPEAKER_01 |
transcript.pyannote[170].start |
704.71409375 |
transcript.pyannote[170].end |
705.15284375 |
transcript.pyannote[171].speaker |
SPEAKER_00 |
transcript.pyannote[171].start |
705.28784375 |
transcript.pyannote[171].end |
709.05096875 |
transcript.pyannote[172].speaker |
SPEAKER_01 |
transcript.pyannote[172].start |
709.10159375 |
transcript.pyannote[172].end |
710.45159375 |
transcript.pyannote[173].speaker |
SPEAKER_00 |
transcript.pyannote[173].start |
710.75534375 |
transcript.pyannote[173].end |
713.59034375 |
transcript.pyannote[174].speaker |
SPEAKER_01 |
transcript.pyannote[174].start |
713.69159375 |
transcript.pyannote[174].end |
717.85971875 |
transcript.pyannote[175].speaker |
SPEAKER_00 |
transcript.pyannote[175].start |
714.13034375 |
transcript.pyannote[175].end |
714.50159375 |
transcript.pyannote[176].speaker |
SPEAKER_00 |
transcript.pyannote[176].start |
717.85971875 |
transcript.pyannote[176].end |
718.70346875 |
transcript.pyannote[177].speaker |
SPEAKER_00 |
transcript.pyannote[177].start |
719.44596875 |
transcript.pyannote[177].end |
723.05721875 |
transcript.pyannote[178].speaker |
SPEAKER_00 |
transcript.pyannote[178].start |
723.47909375 |
transcript.pyannote[178].end |
725.94284375 |
transcript.pyannote[179].speaker |
SPEAKER_01 |
transcript.pyannote[179].start |
724.76159375 |
transcript.pyannote[179].end |
725.20034375 |
transcript.pyannote[180].speaker |
SPEAKER_01 |
transcript.pyannote[180].start |
725.84159375 |
transcript.pyannote[180].end |
726.19596875 |
transcript.pyannote[181].speaker |
SPEAKER_00 |
transcript.pyannote[181].start |
726.22971875 |
transcript.pyannote[181].end |
726.85409375 |
transcript.pyannote[182].speaker |
SPEAKER_01 |
transcript.pyannote[182].start |
726.92159375 |
transcript.pyannote[182].end |
728.79471875 |
transcript.pyannote[183].speaker |
SPEAKER_00 |
transcript.pyannote[183].start |
728.33909375 |
transcript.pyannote[183].end |
731.83221875 |
transcript.pyannote[184].speaker |
SPEAKER_01 |
transcript.pyannote[184].start |
730.11096875 |
transcript.pyannote[184].end |
731.47784375 |
transcript.pyannote[185].speaker |
SPEAKER_01 |
transcript.pyannote[185].start |
732.00096875 |
transcript.pyannote[185].end |
733.41846875 |
transcript.whisperx[0].start |
0.089 |
transcript.whisperx[0].end |
1.55 |
transcript.whisperx[0].text |
接下來請謝依鳳委員質詢謝謝主席我想要請陳部長請陳部長委員好 |
transcript.whisperx[1].start |
20.324 |
transcript.whisperx[1].end |
37.495 |
transcript.whisperx[1].text |
部長我看到你說對於農業保險的這個就是說我們希望修正的在6年以後就是降低成補助就是可以達60%這個上限你不建議拿掉是不是是 |
transcript.whisperx[2].start |
39.136 |
transcript.whisperx[2].end |
66.218 |
transcript.whisperx[2].text |
我覺得說我們今天在討論因為六年快到了嘛我們必須要來討論嘛那今天討論的很多委員所講的就是覆蓋率不高的問題是不是那你認為拿掉這個60%的上限對於法律沒有一個確定性讓公務人員也沒有遵循的標準那我們還有幾種修法啊 |
transcript.whisperx[3].start |
66.798 |
transcript.whisperx[3].end |
81.601 |
transcript.whisperx[3].text |
對不對我們畢竟在這個目前這個農業保險沒有一個像我們來提到說保單的這個品項沒有辦法涵蓋全方面例如 |
transcript.whisperx[4].start |
82.382 |
transcript.whisperx[4].end |
95.886 |
transcript.whisperx[4].text |
像我們今年彰化縣的荔枝因為低溫灼果不成所以導致於產量受損但是過去的農業保險的保單內容只有舊氣溫太高 |
transcript.whisperx[5].start |
99.207 |
transcript.whisperx[5].end |
121.923 |
transcript.whisperx[5].text |
相關性來提出相關的保單而沒有對於氣溫太低造成灼果不易產生產果量不足這樣子的一個情況給予他的一個保單的內容嗎那這個部分你們未來怎麼樣子來提供相關的保單呢 |
transcript.whisperx[6].start |
122.783 |
transcript.whisperx[6].end |
130.395 |
transcript.whisperx[6].text |
我想非常謝謝委員的一個提問特別是委員提這樣的一個案子其實也讓我們有機會能夠重新去思考 |
transcript.whisperx[7].start |
131.209 |
transcript.whisperx[7].end |
160.629 |
transcript.whisperx[7].text |
那因為委員的版本把六年以下的劃掉了以後然後第二項又加了前項要去做滾動檢討嘛那變成前項只有變成前面五年而已前面五年已經過了就還是我們增加就是說增加就是說六年或者是把它留著以後然後第二項說要做滾動的檢討這第一個第二個部分我覺得委員一個重要的精神我們有catch到就是說 |
transcript.whisperx[8].start |
161.829 |
transcript.whisperx[8].end |
172.096 |
transcript.whisperx[8].text |
我們要協助在某一個條件之下讓農民的保費能夠少繳一點那我們是希望用什麼用 |
transcript.whisperx[9].start |
173.191 |
transcript.whisperx[9].end |
200.474 |
transcript.whisperx[9].text |
一個條件我舉個例子他如果每年都從事同樣作物的保險的時候那相對的他的保費是可以打折的我們用保費打折的概念會讓農民有一個另外一個誘因我不是跟天氣對賭今年好像颱風會來我就來保明年好像機會不大就不保我希望他們是一個持續性的投保那這樣子的話保險的覆蓋力不是保險的整個分擔風險的 |
transcript.whisperx[10].start |
202.071 |
transcript.whisperx[10].end |
212.749 |
transcript.whisperx[10].text |
程度會變大那如果說連續兩年或連續三年都有保的時候我的保費的打折的比例我可以調整那這樣其實也達到委員的目的就是 |
transcript.whisperx[11].start |
213.598 |
transcript.whisperx[11].end |
237.246 |
transcript.whisperx[11].text |
因為保費打折也要等於政府增加嘛那其實也是達到同仁的目的但是對農民來講喔不會造成農民說這都建物來出了後我就不要去管理了不要去幹什麼可是問題是目前我們在涵蓋率不足的情況下我們就已經到了這個六年要就是降低成就是保費補助只能60%的上限嘛 |
transcript.whisperx[12].start |
238.846 |
transcript.whisperx[12].end |
264.922 |
transcript.whisperx[12].text |
那當然對於農民的這樣的投保率以及我們希望拉高這個就是農業保險的覆蓋率那會不會也有相關的你知道嗎農民也會覺得說未來整個保費的補助以及相關的誘因不足的情況下那我們怎麼樣子來增加農民的提保率有可能他們就不要啊 |
transcript.whisperx[13].start |
265.622 |
transcript.whisperx[13].end |
293.72 |
transcript.whisperx[13].text |
所以我才會說我們現在更重要的作為是提高保單的品質去設計一些真正的符合農民需求的而且每一張保單你提到了設計保單那今天我們金管會的保險局也有來那對於農民的保單的設計那當然了會不會我們產業界的就是說所有的保險公司他們不願意共同的投入會不會 |
transcript.whisperx[14].start |
294.82 |
transcript.whisperx[14].end |
314.949 |
transcript.whisperx[14].text |
我先跟委員說明也許金管會等一下再說明我覺得現在我們遇到的商業的保險公司其實他都還蠻樂意配合政策的那現在很重要一點就是我們保險的風險有沒有過去累積的資料並不夠長所以他在有限的資料去設計的時候那個風險值會變高 |
transcript.whisperx[15].start |
317.45 |
transcript.whisperx[15].end |
338.019 |
transcript.whisperx[15].text |
風險值一變高的時候保費就會變高保費變高的時候農民看到這個保費也不想保了所以變成一個惡性循環但是隨著時間拉長你的保險本身的數據的累積夠多的時候就能夠趨近於一個比較合理的風險值而且我們會看就像剛才委員有提到的 |
transcript.whisperx[16].start |
338.399 |
transcript.whisperx[16].end |
357.3 |
transcript.whisperx[16].text |
如果商業型保單現在平均的理賠率47那47我剛才說的好的理賠率應該是70到80包括可以扣除它的成本那如果比較低的話我們就會希望它能夠降低保費做一個動態的調整那這個東西就是我們現在在努力的 |
transcript.whisperx[17].start |
357.5 |
transcript.whisperx[17].end |
379.983 |
transcript.whisperx[17].text |
但是對啊這是你們農業部期待的方向嗎但是商業保險這些保險公司有沒有辦法共同配合國家的政策嗎這也是我們在下一波應該要共同來檢討的嗎那你說到了去年的我看到你說去年我們的天然災害救助的八十幾億 |
transcript.whisperx[18].start |
381.164 |
transcript.whisperx[18].end |
403.62 |
transcript.whisperx[18].text |
去年的災損是多少錢我的資料只有到112年112年是150億左右那隨著氣候變遷的條件因此加劇的情況下會不會導致於我們天然災害的這個受損的金額越來越高呢你有觀察到相關的趨勢嗎 |
transcript.whisperx[19].start |
405.485 |
transcript.whisperx[19].end |
423.721 |
transcript.whisperx[19].text |
這個趨勢一定是逐步的上升啦等於說我們現在的像去年上個颱風那今年還沒有到颱風季真的颱風來我們已經因為低溫有沒有造成一些開花不結果的這個品項公告的品項有超過60項已經蠻高了表示說 |
transcript.whisperx[20].start |
425.852 |
transcript.whisperx[20].end |
440.422 |
transcript.whisperx[20].text |
就是極端的天后造成農業經營不確定性越來越高這個越來越高的時候以去年大概農損大概500多億那我相信今年也不會太低啦以現在的天后來講也不會太低所以 |
transcript.whisperx[21].start |
441.122 |
transcript.whisperx[21].end |
455.952 |
transcript.whisperx[21].text |
當我們加入了農業保險這樣的項目能不能共同的來就是說來幫助我們涵蓋所有受災農民的這樣子的一個就是 |
transcript.whisperx[22].start |
456.892 |
transcript.whisperx[22].end |
474.622 |
transcript.whisperx[22].text |
受災的金額有沒有辦法共同來協助這就是我們未來的目標我們會再跟商業保險公司剛才也有委員提到農會也是一個可以承保的單位那農會跟農民的互動會更好也許我們可以共同努力還有一個重點就是 |
transcript.whisperx[23].start |
475.402 |
transcript.whisperx[23].end |
493.536 |
transcript.whisperx[23].text |
中央跟地方因為農業部現在出百分一般都出二分之一那有些品項是地區型的品項地方政府會再加碼甚至於加了百分之三十百分之四十所以農民有時候只負擔百分之十百分之二十所以這個比例在這個法定其實 |
transcript.whisperx[24].start |
494.617 |
transcript.whisperx[24].end |
509.718 |
transcript.whisperx[24].text |
我覺得它不會影響到中央跟地方的合作啦所以後續我想我們一定會透過中央跟地方的合作如果適當的品項的時候看怎麼樣去協助農民來做這個分擔如果風險高的話也許它的比例可以提高一點 |
transcript.whisperx[25].start |
510.379 |
transcript.whisperx[25].end |
525.693 |
transcript.whisperx[25].text |
好還有你說了你去年你就答應我了今年你三個豬瘟都拔針了你說我們拔針的時候台灣的稻谷是不是可以輸到日本 |
transcript.whisperx[26].start |
526.725 |
transcript.whisperx[26].end |
542.638 |
transcript.whisperx[26].text |
臺灣在什麼 稻谷 稻桿對 我們現在也在處理這個區塊因為臺灣的稻草啦對 稻草 稻桿嘛 做榻榻米的那個我們現在已經在談了因為當初他們有一個理由就是因為我們還有這些傳統豬瘟存在 |
transcript.whisperx[27].start |
544.099 |
transcript.whisperx[27].end |
568.807 |
transcript.whisperx[27].text |
那現在沒有了包括我們的豬肉的生煎豬肉的削日本還有相關的稻草的削日其實他們也蠻需要業者蠻需要的做榻榻米啊那些東西所以我們同步已經在跟他們在談而且我們自己也可以處理我們的農費嘛對不對減少減少那個人家燒稻感吧委員關憲的我們一直在做啦那現在目前進行了怎樣喔談判的東西齁 |
transcript.whisperx[28].start |
570.285 |
transcript.whisperx[28].end |
594.553 |
transcript.whisperx[28].text |
還要再跟他們爐啦還沒爐成功是不是這個要繼續努力啦還有啊剛才有委員提到我們彰化的194號米是你們農改廠出來的啊是不是是不是也應該要共同的推銷到日本嘛它的那個米相跟傳統的日本米的米相是不一樣的不是月光米的那種品種我跟委員報告我們現在有個想法就是 |
transcript.whisperx[29].start |
595.333 |
transcript.whisperx[29].end |
622.91 |
transcript.whisperx[29].text |
我們會針對不同地區的特色米會建立地區的品牌然後會跟日方的通路做連結像今年二月初我們就邀請了日方的幾個大的商社來台灣然後我們有做了一個簡單的媒合讓他們了解台灣到底有多少種米讓他們試吃可是他們有擴大嘛對不對我們台灣米蔬日有擴大對不對 |
transcript.whisperx[30].start |
624.062 |
transcript.whisperx[30].end |
649.653 |
transcript.whisperx[30].text |
沒有 擴大是固定的但是如果說我們的族群鎖定在比較高端的話它的配額外的關稅就算比較高那個售價還是有利潤的啦好那這個部分再麻煩你協助好不好會 一定會要協助我們彰化有非常多的米喔都是可以適合去外銷到日本去的而且要建立特有的品牌啦這個我想我們會來努力好 那那個美國的對等關稅7月8號會談完嗎我們 |
transcript.whisperx[31].start |
653.756 |
transcript.whisperx[31].end |
675.705 |
transcript.whisperx[31].text |
會談完嗎?台美的關稅現在正在談判中那農業部的立場還是一致的就是在確保糧食安全產業永續的情形之下我們會尋求一個雙贏貿易雙贏的一個方法那我們不會放棄水稻讓它變成外界所說的關稅會不會最後要拿我們的農業去換 |
transcript.whisperx[32].start |
677.086 |
transcript.whisperx[32].end |
697.353 |
transcript.whisperx[32].text |
我想我想總統已經宣示了很多次的包括院長也說的農民農漁民優先我們絕對不會犧牲農業來換取工業的一個利益那這個部分一定是國家整體考量那農業部有農業部的堅持我們也一定會堅持那7月8號會出來嗎照理論上應該要一定要出來對啊會嗎 |
transcript.whisperx[33].start |
703.544 |
transcript.whisperx[33].end |
718.467 |
transcript.whisperx[33].text |
我相信會吧會啊我相信因為美國就三個月嘛三個月他就一定要處理啊你覺得會出來嗎那我覺得我們現在正在做積極的談判啊所以你覺得7月8號就是會出來了我希望 |
transcript.whisperx[34].start |
719.54 |
transcript.whisperx[34].end |
730.051 |
transcript.whisperx[34].text |
什麼時候出來不是重點出來的結果是我們能夠大家都很開心的對那才是重點對所以你也不確定7月8號因為談判還在進行當中是不是對好 謝謝 |