IVOD_ID |
162247 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/162247 |
日期 |
2025-06-04 |
會議資料.會議代碼 |
委員會-11-3-20-15 |
會議資料.會議代碼:str |
第11屆第3會期財政委員會第15次全體委員會議 |
會議資料.屆 |
11 |
會議資料.會期 |
3 |
會議資料.會次 |
15 |
會議資料.種類 |
委員會 |
會議資料.委員會代碼[0] |
20 |
會議資料.委員會代碼:str[0] |
財政委員會 |
會議資料.標題 |
第11屆第3會期財政委員會第15次全體委員會議 |
影片種類 |
Clip |
開始時間 |
2025-06-04T14:12:42+08:00 |
結束時間 |
2025-06-04T14:21:48+08:00 |
影片長度 |
00:09:06 |
支援功能[0] |
ai-transcript |
video_url |
https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/dfdeed74d30b9828b18c39670a9c4a215e54a9d8358219465c023702ac6ce1c052fbb683eb77f5d55ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
王鴻薇 |
委員發言時間 |
14:12:42 - 14:21:48 |
會議時間 |
2025-06-04T09:00:00+08:00 |
會議名稱 |
立法院第11屆第3會期財政委員會第15次全體委員會議(事由:一、本院台灣民眾黨黨團,有鑑於行政院主計總處行文各縣市政府,將中央編列給地方政府的一般性補助款自114年度5至12月份分配及撥付數全數改為未分配數,已嚴重違反立法院通案刪減、促進政府資源有效配置之決議精神。中央政府預算編列浮濫,原編列三兆一千億元,立法院通案刪減後仍有二兆九千億餘元之數,為中華民國史上最高之中央政府總預算,本院本於職責審議預算,以督促中央政府增進財務效能、減少不當經濟支出甚至浪費之目的,中央政府不思檢討如何有效節用分配資源,卻意圖慷地方政府之慨,緊縮一般性補助款補助事項,將直轄市、準用直轄市規定之縣及縣(市)基本財政收支差短與定額設算之教育、社會福利及基本設施等改為未分配數,此舉不僅違反原預算刪減提案之意旨,更將嚴重影響地方財政及運作,對地方長期建設造成劇烈衝擊。爰建請院會作成決議:「行政院主計總處應依立法院審議中華民國114年度中央政府總預算案通案刪減之決議意旨,由中央各機關及所屬編列之預算刪減調整,並立即將一般性補助款足額撥付予地方政府。」請公決案。【本案如經院會復議,則不予審查】
二、邀請行政院主計總處陳主計長淑姿、財政部莊部長翠雲、內政部劉部長世芳及法務部就「近十年中央政府依財政收支劃分法、地方制度法等地方政府之補助情形及對均衡地方經濟發展之成效」進行專題報告,並備質詢。) |
transcript.pyannote[0].speaker |
SPEAKER_02 |
transcript.pyannote[0].start |
4.89096875 |
transcript.pyannote[0].end |
7.47284375 |
transcript.pyannote[1].speaker |
SPEAKER_02 |
transcript.pyannote[1].start |
8.31659375 |
transcript.pyannote[1].end |
9.56534375 |
transcript.pyannote[2].speaker |
SPEAKER_02 |
transcript.pyannote[2].start |
9.97034375 |
transcript.pyannote[2].end |
14.91471875 |
transcript.pyannote[3].speaker |
SPEAKER_01 |
transcript.pyannote[3].start |
13.09221875 |
transcript.pyannote[3].end |
14.29034375 |
transcript.pyannote[4].speaker |
SPEAKER_02 |
transcript.pyannote[4].start |
15.33659375 |
transcript.pyannote[4].end |
16.65284375 |
transcript.pyannote[5].speaker |
SPEAKER_02 |
transcript.pyannote[5].start |
17.00721875 |
transcript.pyannote[5].end |
18.62721875 |
transcript.pyannote[6].speaker |
SPEAKER_01 |
transcript.pyannote[6].start |
20.58471875 |
transcript.pyannote[6].end |
21.14159375 |
transcript.pyannote[7].speaker |
SPEAKER_01 |
transcript.pyannote[7].start |
21.32721875 |
transcript.pyannote[7].end |
21.90096875 |
transcript.pyannote[8].speaker |
SPEAKER_00 |
transcript.pyannote[8].start |
21.90096875 |
transcript.pyannote[8].end |
22.00221875 |
transcript.pyannote[9].speaker |
SPEAKER_02 |
transcript.pyannote[9].start |
22.08659375 |
transcript.pyannote[9].end |
25.24221875 |
transcript.pyannote[10].speaker |
SPEAKER_02 |
transcript.pyannote[10].start |
25.56284375 |
transcript.pyannote[10].end |
29.73096875 |
transcript.pyannote[11].speaker |
SPEAKER_02 |
transcript.pyannote[11].start |
30.33846875 |
transcript.pyannote[11].end |
31.11471875 |
transcript.pyannote[12].speaker |
SPEAKER_02 |
transcript.pyannote[12].start |
31.60409375 |
transcript.pyannote[12].end |
34.37159375 |
transcript.pyannote[13].speaker |
SPEAKER_02 |
transcript.pyannote[13].start |
34.65846875 |
transcript.pyannote[13].end |
36.41346875 |
transcript.pyannote[14].speaker |
SPEAKER_02 |
transcript.pyannote[14].start |
36.66659375 |
transcript.pyannote[14].end |
41.27346875 |
transcript.pyannote[15].speaker |
SPEAKER_01 |
transcript.pyannote[15].start |
42.08346875 |
transcript.pyannote[15].end |
47.31471875 |
transcript.pyannote[16].speaker |
SPEAKER_01 |
transcript.pyannote[16].start |
48.00659375 |
transcript.pyannote[16].end |
48.52971875 |
transcript.pyannote[17].speaker |
SPEAKER_01 |
transcript.pyannote[17].start |
48.69846875 |
transcript.pyannote[17].end |
53.52471875 |
transcript.pyannote[18].speaker |
SPEAKER_01 |
transcript.pyannote[18].start |
54.19971875 |
transcript.pyannote[18].end |
68.27346875 |
transcript.pyannote[19].speaker |
SPEAKER_02 |
transcript.pyannote[19].start |
68.88096875 |
transcript.pyannote[19].end |
72.81284375 |
transcript.pyannote[20].speaker |
SPEAKER_01 |
transcript.pyannote[20].start |
73.20096875 |
transcript.pyannote[20].end |
74.97284375 |
transcript.pyannote[21].speaker |
SPEAKER_02 |
transcript.pyannote[21].start |
74.97284375 |
transcript.pyannote[21].end |
86.17784375 |
transcript.pyannote[22].speaker |
SPEAKER_01 |
transcript.pyannote[22].start |
75.98534375 |
transcript.pyannote[22].end |
77.70659375 |
transcript.pyannote[23].speaker |
SPEAKER_00 |
transcript.pyannote[23].start |
77.70659375 |
transcript.pyannote[23].end |
77.72346875 |
transcript.pyannote[24].speaker |
SPEAKER_00 |
transcript.pyannote[24].start |
78.33096875 |
transcript.pyannote[24].end |
78.36471875 |
transcript.pyannote[25].speaker |
SPEAKER_01 |
transcript.pyannote[25].start |
78.36471875 |
transcript.pyannote[25].end |
78.73596875 |
transcript.pyannote[26].speaker |
SPEAKER_00 |
transcript.pyannote[26].start |
78.73596875 |
transcript.pyannote[26].end |
78.75284375 |
transcript.pyannote[27].speaker |
SPEAKER_01 |
transcript.pyannote[27].start |
82.68471875 |
transcript.pyannote[27].end |
83.22471875 |
transcript.pyannote[28].speaker |
SPEAKER_02 |
transcript.pyannote[28].start |
86.54909375 |
transcript.pyannote[28].end |
86.98784375 |
transcript.pyannote[29].speaker |
SPEAKER_01 |
transcript.pyannote[29].start |
86.98784375 |
transcript.pyannote[29].end |
93.29909375 |
transcript.pyannote[30].speaker |
SPEAKER_02 |
transcript.pyannote[30].start |
87.07221875 |
transcript.pyannote[30].end |
87.32534375 |
transcript.pyannote[31].speaker |
SPEAKER_01 |
transcript.pyannote[31].start |
94.17659375 |
transcript.pyannote[31].end |
97.33221875 |
transcript.pyannote[32].speaker |
SPEAKER_01 |
transcript.pyannote[32].start |
97.68659375 |
transcript.pyannote[32].end |
98.61471875 |
transcript.pyannote[33].speaker |
SPEAKER_01 |
transcript.pyannote[33].start |
99.71159375 |
transcript.pyannote[33].end |
99.96471875 |
transcript.pyannote[34].speaker |
SPEAKER_02 |
transcript.pyannote[34].start |
99.96471875 |
transcript.pyannote[34].end |
103.37346875 |
transcript.pyannote[35].speaker |
SPEAKER_02 |
transcript.pyannote[35].start |
104.23409375 |
transcript.pyannote[35].end |
112.63784375 |
transcript.pyannote[36].speaker |
SPEAKER_02 |
transcript.pyannote[36].start |
112.97534375 |
transcript.pyannote[36].end |
157.87971875 |
transcript.pyannote[37].speaker |
SPEAKER_02 |
transcript.pyannote[37].start |
158.68971875 |
transcript.pyannote[37].end |
171.53159375 |
transcript.pyannote[38].speaker |
SPEAKER_02 |
transcript.pyannote[38].start |
172.24034375 |
transcript.pyannote[38].end |
172.84784375 |
transcript.pyannote[39].speaker |
SPEAKER_02 |
transcript.pyannote[39].start |
173.53971875 |
transcript.pyannote[39].end |
175.66596875 |
transcript.pyannote[40].speaker |
SPEAKER_02 |
transcript.pyannote[40].start |
177.47159375 |
transcript.pyannote[40].end |
178.19721875 |
transcript.pyannote[41].speaker |
SPEAKER_02 |
transcript.pyannote[41].start |
178.41659375 |
transcript.pyannote[41].end |
183.54659375 |
transcript.pyannote[42].speaker |
SPEAKER_00 |
transcript.pyannote[42].start |
183.69846875 |
transcript.pyannote[42].end |
184.18784375 |
transcript.pyannote[43].speaker |
SPEAKER_02 |
transcript.pyannote[43].start |
184.22159375 |
transcript.pyannote[43].end |
186.06096875 |
transcript.pyannote[44].speaker |
SPEAKER_02 |
transcript.pyannote[44].start |
186.34784375 |
transcript.pyannote[44].end |
194.00909375 |
transcript.pyannote[45].speaker |
SPEAKER_00 |
transcript.pyannote[45].start |
195.00471875 |
transcript.pyannote[45].end |
195.37596875 |
transcript.pyannote[46].speaker |
SPEAKER_02 |
transcript.pyannote[46].start |
195.73034375 |
transcript.pyannote[46].end |
196.54034375 |
transcript.pyannote[47].speaker |
SPEAKER_02 |
transcript.pyannote[47].start |
197.63721875 |
transcript.pyannote[47].end |
198.48096875 |
transcript.pyannote[48].speaker |
SPEAKER_00 |
transcript.pyannote[48].start |
200.06721875 |
transcript.pyannote[48].end |
201.28221875 |
transcript.pyannote[49].speaker |
SPEAKER_02 |
transcript.pyannote[49].start |
201.50159375 |
transcript.pyannote[49].end |
207.30659375 |
transcript.pyannote[50].speaker |
SPEAKER_02 |
transcript.pyannote[50].start |
208.53846875 |
transcript.pyannote[50].end |
209.78721875 |
transcript.pyannote[51].speaker |
SPEAKER_02 |
transcript.pyannote[51].start |
210.00659375 |
transcript.pyannote[51].end |
214.90034375 |
transcript.pyannote[52].speaker |
SPEAKER_02 |
transcript.pyannote[52].start |
215.15346875 |
transcript.pyannote[52].end |
216.55409375 |
transcript.pyannote[53].speaker |
SPEAKER_02 |
transcript.pyannote[53].start |
218.52846875 |
transcript.pyannote[53].end |
220.84034375 |
transcript.pyannote[54].speaker |
SPEAKER_02 |
transcript.pyannote[54].start |
223.99596875 |
transcript.pyannote[54].end |
227.42159375 |
transcript.pyannote[55].speaker |
SPEAKER_02 |
transcript.pyannote[55].start |
228.21471875 |
transcript.pyannote[55].end |
231.99471875 |
transcript.pyannote[56].speaker |
SPEAKER_02 |
transcript.pyannote[56].start |
233.39534375 |
transcript.pyannote[56].end |
233.90159375 |
transcript.pyannote[57].speaker |
SPEAKER_00 |
transcript.pyannote[57].start |
233.44596875 |
transcript.pyannote[57].end |
239.45346875 |
transcript.pyannote[58].speaker |
SPEAKER_02 |
transcript.pyannote[58].start |
236.43284375 |
transcript.pyannote[58].end |
238.69409375 |
transcript.pyannote[59].speaker |
SPEAKER_02 |
transcript.pyannote[59].start |
239.09909375 |
transcript.pyannote[59].end |
248.49846875 |
transcript.pyannote[60].speaker |
SPEAKER_02 |
transcript.pyannote[60].start |
249.32534375 |
transcript.pyannote[60].end |
251.02971875 |
transcript.pyannote[61].speaker |
SPEAKER_00 |
transcript.pyannote[61].start |
251.02971875 |
transcript.pyannote[61].end |
266.30159375 |
transcript.pyannote[62].speaker |
SPEAKER_02 |
transcript.pyannote[62].start |
262.25159375 |
transcript.pyannote[62].end |
262.97721875 |
transcript.pyannote[63].speaker |
SPEAKER_02 |
transcript.pyannote[63].start |
266.30159375 |
transcript.pyannote[63].end |
266.36909375 |
transcript.pyannote[64].speaker |
SPEAKER_00 |
transcript.pyannote[64].start |
266.70659375 |
transcript.pyannote[64].end |
266.97659375 |
transcript.pyannote[65].speaker |
SPEAKER_02 |
transcript.pyannote[65].start |
266.97659375 |
transcript.pyannote[65].end |
267.02721875 |
transcript.pyannote[66].speaker |
SPEAKER_00 |
transcript.pyannote[66].start |
267.02721875 |
transcript.pyannote[66].end |
267.82034375 |
transcript.pyannote[67].speaker |
SPEAKER_00 |
transcript.pyannote[67].start |
268.73159375 |
transcript.pyannote[67].end |
278.33346875 |
transcript.pyannote[68].speaker |
SPEAKER_02 |
transcript.pyannote[68].start |
272.03909375 |
transcript.pyannote[68].end |
274.11471875 |
transcript.pyannote[69].speaker |
SPEAKER_02 |
transcript.pyannote[69].start |
275.16096875 |
transcript.pyannote[69].end |
276.32534375 |
transcript.pyannote[70].speaker |
SPEAKER_00 |
transcript.pyannote[70].start |
278.45159375 |
transcript.pyannote[70].end |
285.65721875 |
transcript.pyannote[71].speaker |
SPEAKER_02 |
transcript.pyannote[71].start |
279.26159375 |
transcript.pyannote[71].end |
280.71284375 |
transcript.pyannote[72].speaker |
SPEAKER_02 |
transcript.pyannote[72].start |
280.96596875 |
transcript.pyannote[72].end |
281.03346875 |
transcript.pyannote[73].speaker |
SPEAKER_02 |
transcript.pyannote[73].start |
281.20221875 |
transcript.pyannote[73].end |
281.21909375 |
transcript.pyannote[74].speaker |
SPEAKER_02 |
transcript.pyannote[74].start |
281.30346875 |
transcript.pyannote[74].end |
286.11284375 |
transcript.pyannote[75].speaker |
SPEAKER_02 |
transcript.pyannote[75].start |
286.56846875 |
transcript.pyannote[75].end |
292.39034375 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
294.82034375 |
transcript.pyannote[76].end |
295.03971875 |
transcript.pyannote[77].speaker |
SPEAKER_02 |
transcript.pyannote[77].start |
295.66409375 |
transcript.pyannote[77].end |
296.64284375 |
transcript.pyannote[78].speaker |
SPEAKER_02 |
transcript.pyannote[78].start |
296.87909375 |
transcript.pyannote[78].end |
303.79784375 |
transcript.pyannote[79].speaker |
SPEAKER_00 |
transcript.pyannote[79].start |
304.23659375 |
transcript.pyannote[79].end |
306.73409375 |
transcript.pyannote[80].speaker |
SPEAKER_02 |
transcript.pyannote[80].start |
305.26596875 |
transcript.pyannote[80].end |
312.48846875 |
transcript.pyannote[81].speaker |
SPEAKER_00 |
transcript.pyannote[81].start |
312.48846875 |
transcript.pyannote[81].end |
312.80909375 |
transcript.pyannote[82].speaker |
SPEAKER_02 |
transcript.pyannote[82].start |
312.80909375 |
transcript.pyannote[82].end |
331.21971875 |
transcript.pyannote[83].speaker |
SPEAKER_00 |
transcript.pyannote[83].start |
321.73596875 |
transcript.pyannote[83].end |
323.55846875 |
transcript.pyannote[84].speaker |
SPEAKER_00 |
transcript.pyannote[84].start |
327.64221875 |
transcript.pyannote[84].end |
328.48596875 |
transcript.pyannote[85].speaker |
SPEAKER_02 |
transcript.pyannote[85].start |
331.30409375 |
transcript.pyannote[85].end |
332.89034375 |
transcript.pyannote[86].speaker |
SPEAKER_02 |
transcript.pyannote[86].start |
333.04221875 |
transcript.pyannote[86].end |
335.18534375 |
transcript.pyannote[87].speaker |
SPEAKER_02 |
transcript.pyannote[87].start |
336.16409375 |
transcript.pyannote[87].end |
339.55596875 |
transcript.pyannote[88].speaker |
SPEAKER_02 |
transcript.pyannote[88].start |
340.51784375 |
transcript.pyannote[88].end |
341.66534375 |
transcript.pyannote[89].speaker |
SPEAKER_02 |
transcript.pyannote[89].start |
342.15471875 |
transcript.pyannote[89].end |
342.18846875 |
transcript.pyannote[90].speaker |
SPEAKER_00 |
transcript.pyannote[90].start |
342.18846875 |
transcript.pyannote[90].end |
342.42471875 |
transcript.pyannote[91].speaker |
SPEAKER_02 |
transcript.pyannote[91].start |
342.42471875 |
transcript.pyannote[91].end |
346.62659375 |
transcript.pyannote[92].speaker |
SPEAKER_00 |
transcript.pyannote[92].start |
342.49221875 |
transcript.pyannote[92].end |
344.41596875 |
transcript.pyannote[93].speaker |
SPEAKER_00 |
transcript.pyannote[93].start |
345.02346875 |
transcript.pyannote[93].end |
348.12846875 |
transcript.pyannote[94].speaker |
SPEAKER_02 |
transcript.pyannote[94].start |
347.09909375 |
transcript.pyannote[94].end |
351.52034375 |
transcript.pyannote[95].speaker |
SPEAKER_02 |
transcript.pyannote[95].start |
351.89159375 |
transcript.pyannote[95].end |
352.39784375 |
transcript.pyannote[96].speaker |
SPEAKER_00 |
transcript.pyannote[96].start |
354.81096875 |
transcript.pyannote[96].end |
355.70534375 |
transcript.pyannote[97].speaker |
SPEAKER_00 |
transcript.pyannote[97].start |
356.31284375 |
transcript.pyannote[97].end |
356.49846875 |
transcript.pyannote[98].speaker |
SPEAKER_00 |
transcript.pyannote[98].start |
356.81909375 |
transcript.pyannote[98].end |
356.88659375 |
transcript.pyannote[99].speaker |
SPEAKER_02 |
transcript.pyannote[99].start |
356.88659375 |
transcript.pyannote[99].end |
356.97096875 |
transcript.pyannote[100].speaker |
SPEAKER_00 |
transcript.pyannote[100].start |
356.97096875 |
transcript.pyannote[100].end |
357.03846875 |
transcript.pyannote[101].speaker |
SPEAKER_02 |
transcript.pyannote[101].start |
357.03846875 |
transcript.pyannote[101].end |
357.13971875 |
transcript.pyannote[102].speaker |
SPEAKER_00 |
transcript.pyannote[102].start |
357.13971875 |
transcript.pyannote[102].end |
357.83159375 |
transcript.pyannote[103].speaker |
SPEAKER_02 |
transcript.pyannote[103].start |
357.29159375 |
transcript.pyannote[103].end |
357.32534375 |
transcript.pyannote[104].speaker |
SPEAKER_02 |
transcript.pyannote[104].start |
357.34221875 |
transcript.pyannote[104].end |
357.56159375 |
transcript.pyannote[105].speaker |
SPEAKER_00 |
transcript.pyannote[105].start |
359.02971875 |
transcript.pyannote[105].end |
360.56534375 |
transcript.pyannote[106].speaker |
SPEAKER_00 |
transcript.pyannote[106].start |
360.86909375 |
transcript.pyannote[106].end |
360.88596875 |
transcript.pyannote[107].speaker |
SPEAKER_02 |
transcript.pyannote[107].start |
360.88596875 |
transcript.pyannote[107].end |
362.48909375 |
transcript.pyannote[108].speaker |
SPEAKER_02 |
transcript.pyannote[108].start |
364.66596875 |
transcript.pyannote[108].end |
365.03721875 |
transcript.pyannote[109].speaker |
SPEAKER_00 |
transcript.pyannote[109].start |
365.03721875 |
transcript.pyannote[109].end |
365.77971875 |
transcript.pyannote[110].speaker |
SPEAKER_02 |
transcript.pyannote[110].start |
365.77971875 |
transcript.pyannote[110].end |
365.79659375 |
transcript.pyannote[111].speaker |
SPEAKER_00 |
transcript.pyannote[111].start |
365.79659375 |
transcript.pyannote[111].end |
365.81346875 |
transcript.pyannote[112].speaker |
SPEAKER_00 |
transcript.pyannote[112].start |
366.42096875 |
transcript.pyannote[112].end |
367.07909375 |
transcript.pyannote[113].speaker |
SPEAKER_00 |
transcript.pyannote[113].start |
367.18034375 |
transcript.pyannote[113].end |
374.85846875 |
transcript.pyannote[114].speaker |
SPEAKER_02 |
transcript.pyannote[114].start |
371.21346875 |
transcript.pyannote[114].end |
374.16659375 |
transcript.pyannote[115].speaker |
SPEAKER_02 |
transcript.pyannote[115].start |
374.85846875 |
transcript.pyannote[115].end |
374.87534375 |
transcript.pyannote[116].speaker |
SPEAKER_02 |
transcript.pyannote[116].start |
375.28034375 |
transcript.pyannote[116].end |
375.29721875 |
transcript.pyannote[117].speaker |
SPEAKER_00 |
transcript.pyannote[117].start |
375.29721875 |
transcript.pyannote[117].end |
375.97221875 |
transcript.pyannote[118].speaker |
SPEAKER_02 |
transcript.pyannote[118].start |
375.97221875 |
transcript.pyannote[118].end |
379.09409375 |
transcript.pyannote[119].speaker |
SPEAKER_00 |
transcript.pyannote[119].start |
376.25909375 |
transcript.pyannote[119].end |
379.02659375 |
transcript.pyannote[120].speaker |
SPEAKER_02 |
transcript.pyannote[120].start |
379.54971875 |
transcript.pyannote[120].end |
385.87784375 |
transcript.pyannote[121].speaker |
SPEAKER_02 |
transcript.pyannote[121].start |
386.83971875 |
transcript.pyannote[121].end |
388.57784375 |
transcript.pyannote[122].speaker |
SPEAKER_02 |
transcript.pyannote[122].start |
389.97846875 |
transcript.pyannote[122].end |
390.67034375 |
transcript.pyannote[123].speaker |
SPEAKER_02 |
transcript.pyannote[123].start |
391.88534375 |
transcript.pyannote[123].end |
400.64346875 |
transcript.pyannote[124].speaker |
SPEAKER_02 |
transcript.pyannote[124].start |
401.23409375 |
transcript.pyannote[124].end |
405.79034375 |
transcript.pyannote[125].speaker |
SPEAKER_02 |
transcript.pyannote[125].start |
405.92534375 |
transcript.pyannote[125].end |
407.27534375 |
transcript.pyannote[126].speaker |
SPEAKER_02 |
transcript.pyannote[126].start |
407.91659375 |
transcript.pyannote[126].end |
408.65909375 |
transcript.pyannote[127].speaker |
SPEAKER_02 |
transcript.pyannote[127].start |
409.16534375 |
transcript.pyannote[127].end |
410.73471875 |
transcript.pyannote[128].speaker |
SPEAKER_02 |
transcript.pyannote[128].start |
410.92034375 |
transcript.pyannote[128].end |
416.11784375 |
transcript.pyannote[129].speaker |
SPEAKER_02 |
transcript.pyannote[129].start |
416.70846875 |
transcript.pyannote[129].end |
417.94034375 |
transcript.pyannote[130].speaker |
SPEAKER_02 |
transcript.pyannote[130].start |
417.99096875 |
transcript.pyannote[130].end |
420.70784375 |
transcript.pyannote[131].speaker |
SPEAKER_02 |
transcript.pyannote[131].start |
421.70346875 |
transcript.pyannote[131].end |
422.93534375 |
transcript.pyannote[132].speaker |
SPEAKER_02 |
transcript.pyannote[132].start |
423.25596875 |
transcript.pyannote[132].end |
424.97721875 |
transcript.pyannote[133].speaker |
SPEAKER_02 |
transcript.pyannote[133].start |
425.29784375 |
transcript.pyannote[133].end |
429.63471875 |
transcript.pyannote[134].speaker |
SPEAKER_02 |
transcript.pyannote[134].start |
430.52909375 |
transcript.pyannote[134].end |
431.55846875 |
transcript.pyannote[135].speaker |
SPEAKER_00 |
transcript.pyannote[135].start |
430.57971875 |
transcript.pyannote[135].end |
431.33909375 |
transcript.pyannote[136].speaker |
SPEAKER_00 |
transcript.pyannote[136].start |
432.92534375 |
transcript.pyannote[136].end |
439.28721875 |
transcript.pyannote[137].speaker |
SPEAKER_02 |
transcript.pyannote[137].start |
434.49471875 |
transcript.pyannote[137].end |
437.38034375 |
transcript.pyannote[138].speaker |
SPEAKER_02 |
transcript.pyannote[138].start |
438.05534375 |
transcript.pyannote[138].end |
444.02909375 |
transcript.pyannote[139].speaker |
SPEAKER_02 |
transcript.pyannote[139].start |
444.23159375 |
transcript.pyannote[139].end |
445.22721875 |
transcript.pyannote[140].speaker |
SPEAKER_02 |
transcript.pyannote[140].start |
446.44221875 |
transcript.pyannote[140].end |
447.13409375 |
transcript.pyannote[141].speaker |
SPEAKER_00 |
transcript.pyannote[141].start |
447.13409375 |
transcript.pyannote[141].end |
447.15096875 |
transcript.pyannote[142].speaker |
SPEAKER_02 |
transcript.pyannote[142].start |
447.82596875 |
transcript.pyannote[142].end |
448.02846875 |
transcript.pyannote[143].speaker |
SPEAKER_00 |
transcript.pyannote[143].start |
448.02846875 |
transcript.pyannote[143].end |
448.73721875 |
transcript.pyannote[144].speaker |
SPEAKER_02 |
transcript.pyannote[144].start |
450.00284375 |
transcript.pyannote[144].end |
450.01971875 |
transcript.pyannote[145].speaker |
SPEAKER_00 |
transcript.pyannote[145].start |
450.01971875 |
transcript.pyannote[145].end |
450.84659375 |
transcript.pyannote[146].speaker |
SPEAKER_00 |
transcript.pyannote[146].start |
451.35284375 |
transcript.pyannote[146].end |
457.07346875 |
transcript.pyannote[147].speaker |
SPEAKER_02 |
transcript.pyannote[147].start |
455.80784375 |
transcript.pyannote[147].end |
456.92159375 |
transcript.pyannote[148].speaker |
SPEAKER_02 |
transcript.pyannote[148].start |
457.07346875 |
transcript.pyannote[148].end |
461.37659375 |
transcript.pyannote[149].speaker |
SPEAKER_00 |
transcript.pyannote[149].start |
459.68909375 |
transcript.pyannote[149].end |
460.43159375 |
transcript.pyannote[150].speaker |
SPEAKER_00 |
transcript.pyannote[150].start |
461.66346875 |
transcript.pyannote[150].end |
464.05971875 |
transcript.pyannote[151].speaker |
SPEAKER_02 |
transcript.pyannote[151].start |
461.71409375 |
transcript.pyannote[151].end |
466.54034375 |
transcript.pyannote[152].speaker |
SPEAKER_02 |
transcript.pyannote[152].start |
468.12659375 |
transcript.pyannote[152].end |
472.96971875 |
transcript.pyannote[153].speaker |
SPEAKER_02 |
transcript.pyannote[153].start |
473.34096875 |
transcript.pyannote[153].end |
474.50534375 |
transcript.pyannote[154].speaker |
SPEAKER_00 |
transcript.pyannote[154].start |
473.35784375 |
transcript.pyannote[154].end |
475.26471875 |
transcript.pyannote[155].speaker |
SPEAKER_02 |
transcript.pyannote[155].start |
475.88909375 |
transcript.pyannote[155].end |
476.83409375 |
transcript.pyannote[156].speaker |
SPEAKER_00 |
transcript.pyannote[156].start |
477.94784375 |
transcript.pyannote[156].end |
483.34784375 |
transcript.pyannote[157].speaker |
SPEAKER_02 |
transcript.pyannote[157].start |
477.98159375 |
transcript.pyannote[157].end |
488.89971875 |
transcript.pyannote[158].speaker |
SPEAKER_00 |
transcript.pyannote[158].start |
485.89596875 |
transcript.pyannote[158].end |
487.24596875 |
transcript.pyannote[159].speaker |
SPEAKER_02 |
transcript.pyannote[159].start |
489.22034375 |
transcript.pyannote[159].end |
491.24534375 |
transcript.pyannote[160].speaker |
SPEAKER_02 |
transcript.pyannote[160].start |
491.68409375 |
transcript.pyannote[160].end |
495.95346875 |
transcript.pyannote[161].speaker |
SPEAKER_00 |
transcript.pyannote[161].start |
494.35034375 |
transcript.pyannote[161].end |
494.41784375 |
transcript.pyannote[162].speaker |
SPEAKER_00 |
transcript.pyannote[162].start |
494.55284375 |
transcript.pyannote[162].end |
495.56534375 |
transcript.pyannote[163].speaker |
SPEAKER_02 |
transcript.pyannote[163].start |
496.49346875 |
transcript.pyannote[163].end |
498.50159375 |
transcript.pyannote[164].speaker |
SPEAKER_02 |
transcript.pyannote[164].start |
498.87284375 |
transcript.pyannote[164].end |
511.69784375 |
transcript.pyannote[165].speaker |
SPEAKER_02 |
transcript.pyannote[165].start |
512.65971875 |
transcript.pyannote[165].end |
514.49909375 |
transcript.pyannote[166].speaker |
SPEAKER_02 |
transcript.pyannote[166].start |
515.35971875 |
transcript.pyannote[166].end |
517.53659375 |
transcript.pyannote[167].speaker |
SPEAKER_02 |
transcript.pyannote[167].start |
517.95846875 |
transcript.pyannote[167].end |
526.59846875 |
transcript.pyannote[168].speaker |
SPEAKER_02 |
transcript.pyannote[168].start |
526.71659375 |
transcript.pyannote[168].end |
528.13409375 |
transcript.pyannote[169].speaker |
SPEAKER_02 |
transcript.pyannote[169].start |
528.18471875 |
transcript.pyannote[169].end |
534.56346875 |
transcript.pyannote[170].speaker |
SPEAKER_02 |
transcript.pyannote[170].start |
534.96846875 |
transcript.pyannote[170].end |
540.19971875 |
transcript.pyannote[171].speaker |
SPEAKER_02 |
transcript.pyannote[171].start |
540.97596875 |
transcript.pyannote[171].end |
543.86159375 |
transcript.pyannote[172].speaker |
SPEAKER_02 |
transcript.pyannote[172].start |
545.00909375 |
transcript.pyannote[172].end |
545.24534375 |
transcript.pyannote[173].speaker |
SPEAKER_01 |
transcript.pyannote[173].start |
545.24534375 |
transcript.pyannote[173].end |
545.56596875 |
transcript.whisperx[0].start |
4.978 |
transcript.whisperx[0].end |
14.305 |
transcript.whisperx[0].text |
好 謝謝主席我請我們台北市代表 現在是財政局局長嗎那另外就是主計長 |
transcript.whisperx[1].start |
20.646 |
transcript.whisperx[1].end |
46.284 |
transcript.whisperx[1].text |
委員好我先請教我們台北市財政局局長在刪除了台北市的一般補助款之後請問一下台北市的教育經費例如學校的水電費例如親韓學生的營養午餐費有沒有受到影響跟委員報告因為就教育的部分我們被刪了12 |
transcript.whisperx[2].start |
48.847 |
transcript.whisperx[2].end |
66.748 |
transcript.whisperx[2].text |
那在這個包括我們親韓學生的午餐費都可能會受到影響那另外老人的福利也受到很多的影響所以我們在內部討論的時候我們的社會局長教育局長都愁眉苦臉不知道要從何下手 |
transcript.whisperx[3].start |
68.922 |
transcript.whisperx[3].end |
97.004 |
transcript.whisperx[3].text |
我想請問一下清涵學生大概是多少人呢大概有1.6萬戶就是1.6萬戶的清涵學生的營養午餐受到影響然後老人的福利也會受到影響那老人福利主要是在哪一個部分是在包括老人的乘車補助收容安置長照以及包括我們健保自負額的補助等等都受到影響所以 |
transcript.whisperx[4].start |
99.755 |
transcript.whisperx[4].end |
123.832 |
transcript.whisperx[4].text |
按照現在中央這樣一刀砍下去雖然台北市是財政比較好一點因為我所知道像包含宜蘭跟苗栗恐怕都要舉債度日那即便是台北市的話我們其實倒楣的又是我們的孩子跟我們的長者我們過去一直在講就說窮不能窮教育 苦不能苦孩子 |
transcript.whisperx[5].start |
124.312 |
transcript.whisperx[5].end |
149.021 |
transcript.whisperx[5].text |
所以這次這樣砍下去對台北市確實包含我們的長者跟我們的孩子學校會受到影響所以我在這邊也應該呼叫一下我們台北市另外兩位立委吳思瑤委員和吳佩奕委員他們知不支持行政院這樣胡砍亂砍的一個方式然後直接影響到我們台北市的孩子們苦了我們尤其是親韓學生的營養午餐讓他們吃不飽 |
transcript.whisperx[6].start |
153.143 |
transcript.whisperx[6].end |
171.276 |
transcript.whisperx[6].text |
好 我們這些 如果今天這些大人們吃得飽飽的然後呢 那我們的孩子吃不飽這是不是我們民進黨台北市立委兩位立委 他們認為這是應該的好 那我想 我再請教一下我們主計長主計長那個Paul Poe 你準備一下 |
transcript.whisperx[7].start |
178.51 |
transcript.whisperx[7].end |
198.488 |
transcript.whisperx[7].text |
這個法定義務 法律義務支出明細表這是不是主計處提供的是是主計處提供的 對不對那請問在一百一四年度的法律義務支出明細表裡面有沒有對地方的一般補助款有沒有 有有金額多少兩千五百零一 |
transcript.whisperx[8].start |
201.77 |
transcript.whisperx[8].end |
216.334 |
transcript.whisperx[8].text |
兩千五百零一億 對不對那所以這個項目也是你們這次砍的項目嘛 對不對啊 那奇怪了既然是法律義務支出這個是你提供給立法院的嘛 對不對為什麼提供給立法院為什麼要把這個明信表提供給立法院 |
transcript.whisperx[9].start |
224.011 |
transcript.whisperx[9].end |
248.145 |
transcript.whisperx[9].text |
因為告訴我們立法院說這些不能刪嘛 對不對就是你送到立法院來審預算的時候 我們不能砍這些預算 對吧是不是原則上是希望盡量不要刪啦就是不能砍嘛 不然什麼叫做法律義務支出呢就是告訴你立法院這些你不要砍 你不能砍因為它都有相關的法律依據嘛 你們還有法律依據嘛 對不對 |
transcript.whisperx[10].start |
249.686 |
transcript.whisperx[10].end |
267.417 |
transcript.whisperx[10].text |
為什麼立法院不能砍你們行政院可以砍呢因為以往立法院審查還是有刪減的一個案例譬如說國債複息譬如說拆團法兩維權統治所以你們可以砍你自己說是法律義務之初然後你自己砍 |
transcript.whisperx[11].start |
268.769 |
transcript.whisperx[11].end |
284.253 |
transcript.whisperx[11].text |
不是因為我們盡量不要砍但是你不得不的時候你怎麼叫不得不為什麼不得不要去砍到法律因為你要砍636我們的確有問題是這樣子所以有什麼問題呢我們剛才也講請問一下我們刪除了636億裡面有11項這11項裡面有沒有對地方補助有沒有有 |
transcript.whisperx[12].start |
295.697 |
transcript.whisperx[12].end |
300.869 |
transcript.whisperx[12].text |
我們砍掉的636億裡面的桶山一共有11項這11項裡面哪一個是對地方補助 |
transcript.whisperx[13].start |
304.295 |
transcript.whisperx[13].end |
317.419 |
transcript.whisperx[13].text |
她是沒有 但是她說她另外刪減補足那不是就是在你那個所有統刪的項目裡面去統刪嗎統刪項目沒辦法這樣刪統刪項目沒辦法刪 特別費你沒辦法刪對不對請問一下統刪項目裡面有沒有特別費有沒有主管的特別費所以主管特別費沒有刪 沒有辦法刪 |
transcript.whisperx[14].start |
326.921 |
transcript.whisperx[14].end |
352.242 |
transcript.whisperx[14].text |
好 行政院的這些長官的特別費不能刪然後孩子的營養這個親韓學生的這個午餐 營養午餐可以刪你這告訴我這個意思嗎蛤 是不是長官的特別費不能刪好 那我請問一下我請問一下在這個桶山項目裡面有沒有包含公務車的有沒有公務車沒有 |
transcript.whisperx[15].start |
356.872 |
transcript.whisperx[15].end |
385.493 |
transcript.whisperx[15].text |
公務車沒有嗎它是設備級投資啊對啊 相關的設備啊相關的支出啊有沒有它有刪設備級投資但是沒有指定說要刪車輛對 但是包不包含公務車嘛包不包含嘛應該是包含包含好 所以你又告訴我這些行政院高官的公務車不能刪但是呢 親韓學生的營養午餐可以刪 |
transcript.whisperx[16].start |
386.892 |
transcript.whisperx[16].end |
388.335 |
transcript.whisperx[16].text |
因為你告訴我 你這些都不能刪嘛合理嗎 |
transcript.whisperx[17].start |
391.96 |
transcript.whisperx[17].end |
420.356 |
transcript.whisperx[17].text |
我們已經講過這個桶山的項目裡面就是在那十一項啊那十一項裡面沒有對地方的補助款那十一項裡面含有我剛講的包含高官的特資費包含公務車特資費公務車你不能砍你可以砍對地方補助款你可以砍掉對長者不管是敬老老人年金農保的補助或者是 |
transcript.whisperx[18].start |
421.955 |
transcript.whisperx[18].end |
429.461 |
transcript.whisperx[18].text |
親韓學生的這些營養午餐你告訴我就是這些啊 合理嗎還不要講什麼中正路了誒該生不生我問你嘛我問你 主席長主席長我問你當你這樣亂刪的時候刪到親韓學生的營養午餐你覺得你於心何忍 |
transcript.whisperx[19].start |
450.063 |
transcript.whisperx[19].end |
476.665 |
transcript.whisperx[19].text |
你覺得應該嗎如果是我們在處理我們不衛生青函學生的那個午餐啦可是這就是包含他的項目就在這裡面啊對 但是我們可以准結其他不必要的開支啊那請問為什麼你們都不准結其他你們必要的開支呢你們請問一下我們統生項目裡面有沒有包含媒體宣傳會有沒有媒體宣傳會 已經刪了百分之六十了還可不可以刪呢 |
transcript.whisperx[20].start |
480.84 |
transcript.whisperx[20].end |
495.428 |
transcript.whisperx[20].text |
不能刪 又已經刪了百分之六十了特別會也刪百分之六十了我問你喔 高官是不是很多都是做商務艙啊出國會也刪百分之六十了大陸也刪百分之八十了 |
transcript.whisperx[21].start |
496.548 |
transcript.whisperx[21].end |
514.045 |
transcript.whisperx[21].text |
高官坐商務艙不能刪高官的坐車不能刪高官的特製費不能刪但是親韓學生的營養午餐可以刪這就是你們今天亂砍地方補助款最後的結果可惡了真的很可惡 |
transcript.whisperx[22].start |
515.424 |
transcript.whisperx[22].end |
543.613 |
transcript.whisperx[22].text |
你說要用一些補救措施喔請你補救措施最應該要做的就是你們先把你們自己啊先好好重新檢視一下六百多億我不相信欸在中央將近三兆元裡面你說你六百多億你沒有辦法遵截一定要去砍一定要去摳住這些教育費或者社會福利的這些相關費用這個實在是太超過以上 |
transcript.whisperx[23].start |
545.026 |
transcript.whisperx[23].end |
545.538 |
transcript.whisperx[23].text |
謝謝 |