iVOD / 149164

Field Value
IVOD_ID 149164
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/149164
日期 2024-03-01
會議資料.會議代碼 院會-11-1-3
會議資料.會議代碼:str 第11屆第1會期第3次會議
會議資料.屆 11
會議資料.會期 1
會議資料.會次 3
會議資料.種類 院會
會議資料.標題 立法院第11屆第1會期第3次會議
影片種類 Clip
開始時間 2024-03-01T09:26:54+08:00
結束時間 2024-03-01T09:30:16+08:00
影片長度 00:03:22
支援功能[0] ai-transcript
支援功能[1] gazette
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/61498c107f55f9623e284953e543ff5adba0a28dd420b397f8ba9b0039caa7a6b7349d8067d4e87d5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 羅智強
委員發言時間 09:26:54 - 09:30:16
會議時間 2024-03-01T09:00:00+08:00
會議名稱 第11屆第1會期第3次會議(事由:一、對行政院院長提出施政方針及施政報告繼續質詢。 二、3月1日上午9時至10時為國是論壇時間。 三、3月5日下午1時50分至2時30分為處理臨時提案時間。)
gazette.lineno 51
gazette.blocks[0][0] 羅委員智強:(9時26分)主席、行政院的官員們,大家好。首先我要問第一個問題,請問陳建仁院長,蘇丹紅是系統性食安問題,還是個案問題?我們發現含蘇丹紅的辣椒粉產品越來越多且流竄全臺,上游邊境把關的檢驗實際上半年前就驗出來,直到事情鬧大了才說要逐件檢驗。我們的邊境管理就是鬆散、形成了破口,然後延伸成全國性的食安問題,以致人心惶惶。我要問我們的院長,請問這是系統性的食安問題,還是只是個案?
gazette.blocks[0][1] 為什麼要從這個地方來切入?我要跟陳建仁院長說,你上次做的食安報告正好應驗了一句話:還馬英九食安公道的就是陳建仁。陳建仁院長在要做食安報告之前大張旗鼓到處宣揚,說會特別比較馬英九執政跟蔡英文執政對食安的成效。我本來萬分期待,可是我發現從頭到尾你跟大家講,你的食安做得比較好只有一個論點,就是你的系統性食安事件只有兩件,馬英九政府系統性食安事件有7件,所以馬政府是蔡政府的3.5倍。但好笑的是,正當蘇丹紅造成全臺灣恐慌的時候,你的食安報告竟然沒有蘇丹紅在裡面!
gazette.blocks[0][2] 蘇丹紅明顯就是系統性食安問題,你竟可以直接無視,把蘇丹紅的食安事件從報告當中踢出去。照你這種算法,你乾脆把自己算0件,把馬政府算500件好了。你自己去定義系統性食安問題,你當所謂的鴕鳥,把頭埋進沙子裡,就看不見自己的食安問題,而當我在質詢你、我問你食品中毒人數最高的是誰?蔡英文政府每年將近5,000多人,馬政府平均每年少400人,然後你可以說食品不是食安問題!現在請你回答大家,蘇丹紅到底是系統性問題,還是個案?謝謝!
gazette.blocks[1][0] 主席:謝謝羅委員智強的發言。
gazette.blocks[1][1] 接下來我們請登記第10號陳委員昭姿發言。
gazette.agenda.page_end 182
gazette.agenda.meet_id 院會-11-1-3
gazette.agenda.speakers[0] 韓國瑜
gazette.agenda.speakers[1] 葉元之
gazette.agenda.speakers[2] 陳菁徽
gazette.agenda.speakers[3] 丁學忠
gazette.agenda.speakers[4] 吳宗憲
gazette.agenda.speakers[5] 張嘉郡
gazette.agenda.speakers[6] 許宇甄
gazette.agenda.speakers[7] 吳春城
gazette.agenda.speakers[8] 顏寬恒
gazette.agenda.speakers[9] 羅智強
gazette.agenda.speakers[10] 陳昭姿
gazette.agenda.page_start 175
gazette.agenda.meetingDate[0] 2024-03-01
gazette.agenda.gazette_id 1130501
gazette.agenda.agenda_lcidc_ids[0] 1130501_00006
gazette.agenda.meet_name 立法院第11屆第1會期第3次會議紀錄
gazette.agenda.content 國是論壇
gazette.agenda.agenda_id 1130501_00007
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 4.65471875
transcript.pyannote[0].end 8.87346875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 9.12659375
transcript.pyannote[1].end 9.71721875
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 10.86471875
transcript.pyannote[2].end 12.48471875
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 13.88534375
transcript.pyannote[3].end 14.99909375
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 15.55596875
transcript.pyannote[4].end 17.51346875
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 17.95221875
transcript.pyannote[5].end 19.62284375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 19.94346875
transcript.pyannote[6].end 20.92221875
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 22.28909375
transcript.pyannote[7].end 25.59659375
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 27.38534375
transcript.pyannote[8].end 29.42721875
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 30.16971875
transcript.pyannote[9].end 32.05971875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 32.70096875
transcript.pyannote[10].end 33.98346875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 35.18159375
transcript.pyannote[11].end 36.22784375
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 36.36284375
transcript.pyannote[12].end 37.81409375
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 38.32034375
transcript.pyannote[13].end 39.09659375
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 39.70409375
transcript.pyannote[14].end 41.45909375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 42.53909375
transcript.pyannote[15].end 43.41659375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 43.61909375
transcript.pyannote[16].end 44.41221875
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 44.91846875
transcript.pyannote[17].end 45.64409375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 46.06596875
transcript.pyannote[18].end 47.26409375
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 48.73221875
transcript.pyannote[19].end 50.11596875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 50.92596875
transcript.pyannote[20].end 51.73596875
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 52.46159375
transcript.pyannote[21].end 53.52471875
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 54.28409375
transcript.pyannote[22].end 54.79034375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 54.87471875
transcript.pyannote[23].end 58.03034375
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 59.86971875
transcript.pyannote[24].end 60.73034375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 62.13096875
transcript.pyannote[25].end 63.73409375
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 64.35846875
transcript.pyannote[26].end 64.99971875
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 65.84346875
transcript.pyannote[27].end 67.69971875
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 68.22284375
transcript.pyannote[28].end 69.11721875
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 69.52221875
transcript.pyannote[29].end 70.58534375
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 72.07034375
transcript.pyannote[30].end 73.85909375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 74.78721875
transcript.pyannote[31].end 76.87971875
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 78.02721875
transcript.pyannote[32].end 80.35596875
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 81.01409375
transcript.pyannote[33].end 82.43159375
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 83.25846875
transcript.pyannote[34].end 85.08096875
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 86.53221875
transcript.pyannote[35].end 86.83596875
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 87.81471875
transcript.pyannote[36].end 89.13096875
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 89.72159375
transcript.pyannote[37].end 92.57346875
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 93.97409375
transcript.pyannote[38].end 94.90221875
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 95.37471875
transcript.pyannote[39].end 98.09159375
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 98.80034375
transcript.pyannote[40].end 100.80846875
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 101.36534375
transcript.pyannote[41].end 103.55909375
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 104.13284375
transcript.pyannote[42].end 106.54596875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 106.90034375
transcript.pyannote[43].end 107.81159375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 108.38534375
transcript.pyannote[44].end 108.73971875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 109.29659375
transcript.pyannote[45].end 109.87034375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 110.79846875
transcript.pyannote[46].end 112.40159375
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 113.49846875
transcript.pyannote[47].end 118.74659375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 119.59034375
transcript.pyannote[48].end 121.78409375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 122.07096875
transcript.pyannote[49].end 123.43784375
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 124.14659375
transcript.pyannote[50].end 125.93534375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 126.39096875
transcript.pyannote[51].end 127.72409375
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 128.46659375
transcript.pyannote[52].end 128.98971875
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 129.34409375
transcript.pyannote[53].end 131.55471875
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 132.41534375
transcript.pyannote[54].end 135.25034375
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 135.77346875
transcript.pyannote[55].end 141.37596875
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 142.43909375
transcript.pyannote[56].end 145.03784375
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 145.67909375
transcript.pyannote[57].end 148.46346875
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 148.81784375
transcript.pyannote[58].end 150.08346875
transcript.pyannote[59].speaker SPEAKER_00
transcript.pyannote[59].start 150.74159375
transcript.pyannote[59].end 153.47534375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 154.45409375
transcript.pyannote[60].end 155.75346875
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 156.14159375
transcript.pyannote[61].end 160.44471875
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 160.95096875
transcript.pyannote[62].end 163.22909375
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 163.73534375
transcript.pyannote[63].end 166.46909375
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 166.87409375
transcript.pyannote[64].end 169.62471875
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 170.58659375
transcript.pyannote[65].end 175.22721875
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 176.40846875
transcript.pyannote[66].end 177.57284375
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 178.48409375
transcript.pyannote[67].end 183.07409375
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 183.59721875
transcript.pyannote[68].end 186.21284375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 186.71909375
transcript.pyannote[69].end 189.25034375
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 194.43096875
transcript.pyannote[70].end 201.07971875
transcript.whisperx[0].start 4.673
transcript.whisperx[0].end 33.666
transcript.whisperx[0].text 主席然後我們行政院的官員們大家好首先我要問第一個問題陳建仁院長請問蘇丹紅是系統性食安問題還是個案問題蘇丹紅是系統性食安問題還是個案問題我們發現了蘇丹紅的辣椒粉產品越來越多流竄全台
transcript.whisperx[1].start 35.516
transcript.whisperx[1].end 57.472
transcript.whisperx[1].text 從上游我們邊境把關的檢驗實際上半年前就驗出來直到事情鬧大了才說要逐漸檢驗我們的邊境管理就是鬆散形成了破口然後延伸到全國性的食安問題人心惶惶
transcript.whisperx[2].start 62.179
transcript.whisperx[2].end 86.577
transcript.whisperx[2].text 我要問我們的院長請問你這是系統性的食安問題還是只是個案為什麼要從這個地方來切入我要跟陳建仁院長說你上次做的食安報告正好應驗了一句話還馬英九食安的
transcript.whisperx[3].start 87.85
transcript.whisperx[3].end 112.119
transcript.whisperx[3].text 就是陳建仁還馬英九食安公道的就是陳建仁陳建仁在院長在要做食安報告之前大張旗鼓的到處宣揚說我們會特別來比較馬英九執政跟蔡英文執政對食安的成效我本來是萬分期待
transcript.whisperx[4].start 113.544
transcript.whisperx[4].end 141.067
transcript.whisperx[4].text 可是我發現從頭到尾你跟大家講你的食安做得比較好只有一個論點就是你的系統性食安事件只有兩件馬英九政府系統性食安事件有七件所以馬政府是蔡政府的3.5倍但好像是正在蘇丹紅全台灣在恐慌的時候你的食安報告竟然沒有蘇丹紅在裡面
transcript.whisperx[5].start 142.709
transcript.whisperx[5].end 169.03
transcript.whisperx[5].text 蘇丹紅明顯就系統性食安問題你就可以直接無視蘇丹紅把蘇丹紅的這個食安事件從報告當中踢出去照你這種算法你乾脆把自己算零件把政府算500件好了你自己去定義系統性食安問題你當一個所謂的鴕鳥頭埋進沙子裡就看不見自己的食安問題
transcript.whisperx[6].start 170.646
transcript.whisperx[6].end 189.14
transcript.whisperx[6].text 而當我在質詢你我問你說食品中毒人數最高的是誰?蔡英文每年將近5000多人馬政府平均每年少400人然後你可以說食品不是食安問題現在請你回答大家蘇丹紅到底
transcript.whisperx[7].start 195.249
transcript.whisperx[7].end 200.873
transcript.whisperx[7].text 謝謝羅委員智強的發言。接下來我們請登記第10號陳委員昭之發言。