iVOD / 162018

Field Value
IVOD_ID 162018
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/162018
日期 2025-05-28
會議資料.會議代碼 委員會-11-3-15-22
會議資料.會議代碼:str 第11屆第3會期內政委員會第22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 22
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3會期內政委員會第22次全體委員會議
影片種類 Clip
開始時間 2025-05-28T10:21:09+08:00
結束時間 2025-05-28T10:32:20+08:00
影片長度 00:11:11
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/75aba70f567c6f24a1ec0358ecfeb13cd126c33bcaff1fd1a3426710e0a50eed83290c181a374e3b5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 丁學忠
委員發言時間 10:21:09 - 10:32:20
會議時間 2025-05-28T09:00:00+08:00
會議名稱 立法院第11屆第3會期內政委員會第22次全體委員會議(事由:處理114年度中央政府總預算案有關行政院預算解凍案。)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 10.99971875
transcript.pyannote[0].end 28.44846875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 19.42034375
transcript.pyannote[1].end 19.62284375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 28.93784375
transcript.pyannote[2].end 29.64659375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 34.75971875
transcript.pyannote[3].end 34.92846875
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 34.96221875
transcript.pyannote[4].end 34.99596875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 39.16409375
transcript.pyannote[5].end 40.85159375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 41.29034375
transcript.pyannote[6].end 45.08721875
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 45.42471875
transcript.pyannote[7].end 72.74534375
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 73.09971875
transcript.pyannote[8].end 76.03596875
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 76.57596875
transcript.pyannote[9].end 77.53784375
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 78.65159375
transcript.pyannote[10].end 80.86221875
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 81.01409375
transcript.pyannote[11].end 108.36846875
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 109.61721875
transcript.pyannote[12].end 114.30846875
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 115.18596875
transcript.pyannote[13].end 119.79284375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 119.97846875
transcript.pyannote[14].end 120.51846875
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 120.70409375
transcript.pyannote[15].end 122.03721875
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 122.03721875
transcript.pyannote[16].end 122.25659375
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 122.25659375
transcript.pyannote[17].end 122.37471875
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 122.37471875
transcript.pyannote[18].end 122.44221875
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 123.31971875
transcript.pyannote[19].end 123.33659375
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 123.33659375
transcript.pyannote[20].end 123.80909375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 125.46284375
transcript.pyannote[21].end 125.85096875
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 125.96909375
transcript.pyannote[22].end 129.09096875
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 129.37784375
transcript.pyannote[23].end 143.11409375
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 143.36721875
transcript.pyannote[24].end 174.34971875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 159.06096875
transcript.pyannote[25].end 159.36471875
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 172.61159375
transcript.pyannote[26].end 173.11784375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 174.45096875
transcript.pyannote[27].end 175.78409375
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 174.67034375
transcript.pyannote[28].end 185.84159375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 180.54284375
transcript.pyannote[29].end 181.69034375
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 184.05284375
transcript.pyannote[30].end 184.60971875
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 185.57159375
transcript.pyannote[31].end 191.59596875
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 190.70159375
transcript.pyannote[32].end 199.81409375
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 199.81409375
transcript.pyannote[33].end 215.67659375
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 213.28034375
transcript.pyannote[34].end 219.62534375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 219.81096875
transcript.pyannote[35].end 220.85721875
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 222.17346875
transcript.pyannote[36].end 231.45471875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 228.95721875
transcript.pyannote[37].end 229.68284375
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 230.64471875
transcript.pyannote[38].end 233.88471875
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 234.18846875
transcript.pyannote[39].end 238.05284375
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 238.18784375
transcript.pyannote[40].end 238.47471875
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 238.47471875
transcript.pyannote[41].end 238.62659375
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 238.62659375
transcript.pyannote[42].end 238.64346875
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 238.64346875
transcript.pyannote[43].end 238.66034375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 238.66034375
transcript.pyannote[44].end 239.82471875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 240.22971875
transcript.pyannote[45].end 246.65909375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 246.89534375
transcript.pyannote[46].end 246.96284375
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 246.96284375
transcript.pyannote[47].end 247.84034375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 247.84034375
transcript.pyannote[48].end 248.80221875
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 247.97534375
transcript.pyannote[49].end 248.75159375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 248.80221875
transcript.pyannote[50].end 248.81909375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 248.81909375
transcript.pyannote[51].end 248.92034375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 249.12284375
transcript.pyannote[52].end 251.35034375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 255.70409375
transcript.pyannote[53].end 270.03096875
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 268.39409375
transcript.pyannote[54].end 269.32221875
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 270.03096875
transcript.pyannote[55].end 277.86096875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 278.02971875
transcript.pyannote[56].end 279.10971875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 278.06346875
transcript.pyannote[57].end 289.87596875
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 290.17971875
transcript.pyannote[58].end 290.87159375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 291.42846875
transcript.pyannote[59].end 294.58409375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 295.19159375
transcript.pyannote[60].end 310.02471875
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 303.78096875
transcript.pyannote[61].end 303.98346875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 310.12596875
transcript.pyannote[62].end 310.37909375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 310.61534375
transcript.pyannote[63].end 312.21846875
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 312.23534375
transcript.pyannote[64].end 349.32659375
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 349.46159375
transcript.pyannote[65].end 354.57471875
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 354.86159375
transcript.pyannote[66].end 357.17346875
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 357.44346875
transcript.pyannote[67].end 359.23221875
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 360.02534375
transcript.pyannote[68].end 361.13909375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 362.33721875
transcript.pyannote[69].end 369.54284375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 369.74534375
transcript.pyannote[70].end 372.19221875
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 372.34409375
transcript.pyannote[71].end 378.08159375
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 378.23346875
transcript.pyannote[72].end 382.03034375
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 382.95846875
transcript.pyannote[73].end 387.51471875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 387.86909375
transcript.pyannote[74].end 391.21034375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 391.73346875
transcript.pyannote[75].end 393.72471875
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 393.72471875
transcript.pyannote[76].end 393.74159375
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 394.93971875
transcript.pyannote[77].end 403.05659375
transcript.pyannote[78].speaker SPEAKER_01
transcript.pyannote[78].start 397.45409375
transcript.pyannote[78].end 408.96284375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 404.18721875
transcript.pyannote[79].end 405.65534375
transcript.pyannote[80].speaker SPEAKER_02
transcript.pyannote[80].start 408.96284375
transcript.pyannote[80].end 409.14846875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 409.14846875
transcript.pyannote[81].end 409.89096875
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 409.16534375
transcript.pyannote[82].end 418.54784375
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 413.01284375
transcript.pyannote[83].end 432.87471875
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 428.67284375
transcript.pyannote[84].end 429.21284375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 432.72284375
transcript.pyannote[85].end 432.97596875
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 432.97596875
transcript.pyannote[86].end 445.81784375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 446.32409375
transcript.pyannote[87].end 448.90596875
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 449.31096875
transcript.pyannote[88].end 459.68909375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 459.68909375
transcript.pyannote[89].end 459.70596875
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 459.70596875
transcript.pyannote[90].end 461.15721875
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 459.72284375
transcript.pyannote[91].end 473.27346875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 473.81346875
transcript.pyannote[92].end 486.19971875
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 486.53721875
transcript.pyannote[93].end 488.47784375
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 486.57096875
transcript.pyannote[94].end 489.96284375
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 490.48596875
transcript.pyannote[95].end 502.63596875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 490.53659375
transcript.pyannote[96].end 491.04284375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 493.11846875
transcript.pyannote[97].end 495.04221875
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 503.29409375
transcript.pyannote[98].end 508.93034375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 509.67284375
transcript.pyannote[99].end 514.75221875
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 515.41034375
transcript.pyannote[100].end 516.25409375
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 516.32159375
transcript.pyannote[101].end 524.79284375
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 524.52284375
transcript.pyannote[102].end 524.64096875
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 524.79284375
transcript.pyannote[103].end 525.21471875
transcript.pyannote[104].speaker SPEAKER_01
transcript.pyannote[104].start 524.99534375
transcript.pyannote[104].end 536.41971875
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 527.74596875
transcript.pyannote[105].end 528.43784375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 528.55596875
transcript.pyannote[106].end 529.24784375
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 533.36534375
transcript.pyannote[107].end 534.15846875
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 534.15846875
transcript.pyannote[108].end 534.31034375
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 534.71534375
transcript.pyannote[109].end 534.81659375
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 534.81659375
transcript.pyannote[110].end 534.88409375
transcript.pyannote[111].speaker SPEAKER_00
transcript.pyannote[111].start 534.98534375
transcript.pyannote[111].end 535.33971875
transcript.pyannote[112].speaker SPEAKER_01
transcript.pyannote[112].start 536.97659375
transcript.pyannote[112].end 540.48659375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 540.90846875
transcript.pyannote[113].end 554.54346875
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 555.15096875
transcript.pyannote[114].end 562.32284375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 562.42409375
transcript.pyannote[115].end 562.69409375
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 562.79534375
transcript.pyannote[116].end 569.02221875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 569.17409375
transcript.pyannote[117].end 580.15971875
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 580.53096875
transcript.pyannote[118].end 581.91471875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 582.74159375
transcript.pyannote[119].end 584.63159375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 584.96909375
transcript.pyannote[120].end 585.88034375
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 586.20096875
transcript.pyannote[121].end 588.04034375
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 588.79971875
transcript.pyannote[122].end 589.32284375
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 590.11596875
transcript.pyannote[123].end 592.47846875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 592.66409375
transcript.pyannote[124].end 601.05096875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 601.54034375
transcript.pyannote[125].end 603.02534375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 603.71721875
transcript.pyannote[126].end 604.99971875
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 605.77596875
transcript.pyannote[127].end 609.25221875
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 609.58971875
transcript.pyannote[128].end 611.59784375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 611.93534375
transcript.pyannote[129].end 616.81221875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 617.57159375
transcript.pyannote[130].end 622.04346875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 622.26284375
transcript.pyannote[131].end 628.77659375
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 628.92846875
transcript.pyannote[132].end 630.19409375
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 630.31221875
transcript.pyannote[133].end 630.97034375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 631.15596875
transcript.pyannote[134].end 633.60284375
transcript.pyannote[135].speaker SPEAKER_01
transcript.pyannote[135].start 633.97409375
transcript.pyannote[135].end 638.17596875
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 638.74971875
transcript.pyannote[136].end 658.98284375
transcript.pyannote[137].speaker SPEAKER_01
transcript.pyannote[137].start 659.23596875
transcript.pyannote[137].end 662.44221875
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 662.83034375
transcript.pyannote[138].end 662.84721875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 662.84721875
transcript.pyannote[139].end 662.99909375
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 662.99909375
transcript.pyannote[140].end 663.04971875
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 664.01159375
transcript.pyannote[141].end 668.71971875
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 669.37784375
transcript.pyannote[142].end 670.96409375
transcript.whisperx[0].start 10.998
transcript.whisperx[0].end 27.201
transcript.whisperx[0].text 好,感謝主席,我剛才在單日就位才開始講好,這樣讓我們的秘書長休息一下我請我們的主計處旅處長跟我們行政院主計總處公務預算處的專門委員好,請兩位
transcript.whisperx[1].start 39.398
transcript.whisperx[1].end 51.729
transcript.whisperx[1].text 處長,地方公所的特殊單位是縣政府,所以他們的分配款是由縣政府分配給我們地方公所,對嗎?他們是在替我們地方公所做委員、學務的第一算,也替我們縣政府來做到郡鄉鎮的一個發展的一個規劃
transcript.whisperx[2].start 63.098
transcript.whisperx[2].end 65.742
transcript.whisperx[2].text 我們婦女館政府 國管局政府 他們的直屬單位就是中央立法院 行政院他們的直屬單位是不是所以
transcript.whisperx[3].start 78.7
transcript.whisperx[3].end 94.811
transcript.whisperx[3].text 他們都替我們行政院 當了解到地方的需求 了解地方需要建設 了解地方跟阿拉川省 整個省下來向中央來告告到地方的需求來向中央來請出經費 來替我們地方來建設還有 當我們這個統籌分配款 這也是過去一直以來就是都由中央來支付給我們管理政府的 這也是正確的
transcript.whisperx[4].start 109.673
transcript.whisperx[4].end 122.091
transcript.whisperx[4].text 正確嗎 正確 當這次的綜藝省裡面 我會記得當我們這個工作給我們地方的同儲分配款是一甲都沒有刪掉嗎 對嗎
transcript.whisperx[5].start 126.195
transcript.whisperx[5].end 142.704
transcript.whisperx[5].text 報告委員主委總書這邊跟您說明一下就是在我國的這個政府的體系裡面來講的話中央政府跟地方政府都是獨立的公法人都是獨立有民選去運作的所以地方政府雲林縣政府他本來就要依照地方制度法去
transcript.whisperx[6].start 143.504
transcript.whisperx[6].end 158.525
transcript.whisperx[6].text 去實施他的地方自治事項那地方自治事項該負擔的經費也要由雲林縣政府來負擔那只是說有時候可能在地方政府在裁員上面有所困難的時候所以他需要中央來做協助所以中央在預算裡面會編列補助款
transcript.whisperx[7].start 160.647
transcript.whisperx[7].end 189.787
transcript.whisperx[7].text 所以補助款只是說是地方政府的事情那我中央在財政上給予支援那這支援必須要看我中央的財政能力的狀況我可以支援到什麼狀況那理論上地方政府的該補關的錢你這樣說我們政府我們政府稅收的稅金我們就可以自己留著就好了是沒錯我們可以自己留著我們不用上繳中央國庫如果再依照這個財務法規定的地方稅當然是地方收地方去用沒錯
transcript.whisperx[8].start 190.527
transcript.whisperx[8].end 191.028
transcript.whisperx[8].text 只是裡面有一個統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統統
transcript.whisperx[9].start 219.911
transcript.whisperx[9].end 220.453
transcript.whisperx[9].text 依靠你了
transcript.whisperx[10].start 222.533
transcript.whisperx[10].end 249.623
transcript.whisperx[10].text 我跟委員報告這個統籌分配稅款是可能就是從所得稅提撥出來或會務稅跟這個土地政治稅提撥出來你建議區議會讓我們分明管政府多少個統籌分配稅款是財政部負責他不編入我們中央政府的總預算不是我們主計處加不是是財政部負責的我們主計處這邊是代行政院在處理這個一般性補助款的部分一般性補助款的部分好這樣我就請我們基屬長
transcript.whisperx[11].start 256.429
transcript.whisperx[11].end 277.511
transcript.whisperx[11].text 因為中央政府的預算裡面是不包含統籌分配因為統籌分配他是按照公式所以公式訂了以後該給多少財政部就直接撥給了地方政府那一定是有預計說明年要多少要給地方多少今年就要預計好還是今年就要規劃好的啊
transcript.whisperx[12].start 278.252
transcript.whisperx[12].end 292.903
transcript.whisperx[12].text 因為投資分配款基本上它有一個公式它等到相關的一些稅的結果出來按照那個公式就知道說每一個縣市可以分配多少不是這樣啦我們那一年
transcript.whisperx[13].start 295.245
transcript.whisperx[13].end 299.627
transcript.whisperx[13].text 我們中央政府要構造我們地方的這個同儲分配款喔其實那當今一年就都計算好了是啊是啊當今一年計算好了是啊我們今年我們中央要給我們分離的同儲分配款總共是一百三十七億是
transcript.whisperx[14].start 310.872
transcript.whisperx[14].end 318.218
transcript.whisperx[14].text 一共有37億啦對啊 結果我們黨 我們這個中央政府我們整個的綜藝省我們將對這個統籌分配款將對在國際的綜藝省的股份我們一戶人都有去刪除到就是代表說可以順利讓我們中央教醫院一樣繼續構造我們地方的統籌分配款可以讓他們順利來執行到
transcript.whisperx[15].start 339.535
transcript.whisperx[15].end 346.758
transcript.whisperx[15].text 我們之前的一些學務甚至學歷也好結果今年我們婦人館政府不要說婦人館政府而已啦全國的國管制我們行政院主動給三點二十七點三二塊婦人館的薪三十七塊六塊喔三十七億六啦三十七億六啦
transcript.whisperx[16].start 362.366
transcript.whisperx[16].end 364.548
transcript.whisperx[16].text 我們要基礎建設,我們要照顧到我們這裡福利的,我們要跟法官有聯絡的情緒,我們一個省管有辦法一個省37億人
transcript.whisperx[17].start 383.001
transcript.whisperx[17].end 386.566
transcript.whisperx[17].text 這對我們婦人館長今年後半年來要來執行到我們公屋要來執行到社會福利這樣是要怎麼執行這樣可以這樣把我們關起來
transcript.whisperx[18].start 394.98
transcript.whisperx[18].end 401.142
transcript.whisperx[18].text 報告委員說老實話我們也覺得非常無奈大體通商的939億你說立法院選中央議員綜商不是每年才發生的綜商是每一年都發生但是那個額度都很小很小我們有辦法自己去調整你們有什麼問題你們可以比加強議員有什麼問題我主席對著我們今天的行政院我們這個中議省的解答案真的我們都很樂觀
transcript.whisperx[19].start 424.989
transcript.whisperx[19].end 442.015
transcript.whisperx[19].text 你看國會都在解凍,國會都在解凍,有沒有遇到什麼困難?有疑問的大家再研究討論對啊,我們也是希望說,因為這經費對於行政單位來說是非常重要的醫生對於行政單位來說,真的是非常要緊的所以我們知道說,醫生的重要性
transcript.whisperx[20].start 449.358
transcript.whisperx[20].end 472.826
transcript.whisperx[20].text 啊再加上我們會替中央政府消防衛生的重要性再加上我們地方管理政府的衛生的重要性這個道義在哪裡?這個公平性在哪裡?事實上我們中央政府對於地方政府事實上是大力支持所以如果加上您剛才提到的統籌分配本一般補助還有計劃型補助事實上我們編列的預算是總共加起來是超過一兆
transcript.whisperx[21].start 473.866
transcript.whisperx[21].end 488.093
transcript.whisperx[21].text 那個都是要來支持地方的那但是因為我們中央政府的預算被砍那麼多的情況之下而且有這麼一大筆的六百多億必須要自行參選的情況之下這個做老實話是不如奈 這是統三的過分啊統三的過分啊 是啊 是啊我們秘書長在說是統三的過分統三就是九百三十九億啊 統三是由我們國國會全體國際的基礎或是全體府間或是從府間內我們可以下去去參選
transcript.whisperx[22].start 503.737
transcript.whisperx[22].end 508.465
transcript.whisperx[22].text 不是說統三就是叫你們來統三管治政府的這個分科的款這樣我們管治政府再來後面的年度是要怎麼再繼續經營下去
transcript.whisperx[23].start 515.878
transcript.whisperx[23].end 529.511
transcript.whisperx[23].text 我知道這件事不是秘書長你可以有辦法做決定我還要推動政府歡迎給你們聽還有一人 不好意思 還有我花一兩分鐘的時間來 董委員剛才有在把我們秘書長提起的我們這個高中的產業研修這檔一掛十年的時候 那時候我們秘書長在做
transcript.whisperx[24].start 541.002
transcript.whisperx[24].end 543.305
transcript.whisperx[24].text 政府委員兼國會主任那時候是高中產業園區合併的時期我剛才聽到有院長和經濟局長討論盡快推動高中產業園區
transcript.whisperx[25].start 559.713
transcript.whisperx[25].end 567.855
transcript.whisperx[25].text 除了炸高中就要發電了炸高中就要發電在這30年你們學生管政府已經去招商都很好了都很好了產業也在進駐管政府也一直在開始在發表到我們這個產業園區的這個工程啊希望遇到一個選舉天災地變來一切天災天災平平全都不一樣的這個高中產業園區
transcript.whisperx[26].start 588.854
transcript.whisperx[26].end 591.435
transcript.whisperx[26].text 現在要變成那時候是九十幾個九十幾個做第一期讓我們婦人館政府環境就可以馬上進行現在說要一、兩個七十個開始進行推動我也是
transcript.whisperx[27].start 605.839
transcript.whisperx[27].end 613.926
transcript.whisperx[27].text 支持啦 我也是支持啦 既然社會已經煮成功了 我也是支持我們現在一兩百七十甲下去推動但是風勢 風勢要怎麼加快 要怎麼讓我們電影的發展會更快這就是要靠我們中央 我們行政院 我們經濟局 我們農業局來專利來跟我們合作啦 國 真正的
transcript.whisperx[28].start 630.459
transcript.whisperx[28].end 637.602
transcript.whisperx[28].text 現在年輕人有機會越來越少出外越多當我們故鄉的林考所越來越老年化年輕人的感覺在故鄉沒有機會這也不是你們想要看的也不是我們想期待的我們要把地方發生的事情要順便讓你們知道我們要替我們地方跟我們中央做一個溝通的橋樑希望我們過這個橋過到那邊下來的時候給你們的訊息希望你們可以
transcript.whisperx[29].start 659.612
transcript.whisperx[29].end 659.752
transcript.whisperx[29].text 謝謝主席