iVOD / 159351

Field Value
IVOD_ID 159351
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/159351
日期 2025-03-19
會議資料.會議代碼 委員會-11-3-26-3
會議資料.會議代碼:str 第11屆第3會期社會福利及衛生環境委員會第3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 3
會議資料.種類 委員會
會議資料.委員會代碼[0] 26
會議資料.委員會代碼:str[0] 社會福利及衛生環境委員會
會議資料.標題 第11屆第3會期社會福利及衛生環境委員會第3次全體委員會議
影片種類 Clip
開始時間 2025-03-19T10:54:42+08:00
結束時間 2025-03-19T11:03:25+08:00
影片長度 00:08:43
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/8d8da86eec6b25b882749268f829eb8239fe1519e09d1f6f9ba850061ce77509e7bc962e133d59975ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 蘇清泉
委員發言時間 10:54:42 - 11:03:25
會議時間 2025-03-19T09:00:00+08:00
會議名稱 立法院第11屆第3會期社會福利及衛生環境委員會第3次全體委員會議(事由:一、邀請勞動部部長列席報告業務概況,並備質詢。 二、處理113年度中央政府總預算附屬單位預算決議有關勞動部預算凍結報告案19案。【報告事項】【如經復議則不予處理】 三、繼續審查114年度中央政府總預算案附屬單位預算關於勞動部主管部分。 【3月17日、19日及20日三天一次會】)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 0.03096875
transcript.pyannote[0].end 1.02659375
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 1.02659375
transcript.pyannote[1].end 1.38096875
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 1.78596875
transcript.pyannote[2].end 2.03909375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 7.79346875
transcript.pyannote[3].end 11.30346875
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 17.64846875
transcript.pyannote[4].end 17.66534375
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 17.66534375
transcript.pyannote[5].end 23.48721875
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 24.87096875
transcript.pyannote[6].end 27.33471875
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 27.40221875
transcript.pyannote[7].end 27.70596875
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 28.48221875
transcript.pyannote[8].end 29.56221875
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 28.60034375
transcript.pyannote[9].end 28.88721875
transcript.pyannote[10].speaker SPEAKER_02
transcript.pyannote[10].start 29.91659375
transcript.pyannote[10].end 31.43534375
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 30.92909375
transcript.pyannote[11].end 31.24971875
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 33.74721875
transcript.pyannote[12].end 36.14346875
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 36.88596875
transcript.pyannote[13].end 37.22346875
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 37.54409375
transcript.pyannote[14].end 39.01221875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 39.99096875
transcript.pyannote[15].end 40.86846875
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 41.69534375
transcript.pyannote[16].end 42.25221875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 43.31534375
transcript.pyannote[17].end 45.22221875
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 45.54284375
transcript.pyannote[18].end 49.84596875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 50.21721875
transcript.pyannote[19].end 55.92096875
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 56.91659375
transcript.pyannote[20].end 64.64534375
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 65.38784375
transcript.pyannote[21].end 67.88534375
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 67.93596875
transcript.pyannote[22].end 78.75284375
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 80.08596875
transcript.pyannote[23].end 84.45659375
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 85.06409375
transcript.pyannote[24].end 91.03784375
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 91.25721875
transcript.pyannote[25].end 93.43409375
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 94.19346875
transcript.pyannote[26].end 96.55596875
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 97.39971875
transcript.pyannote[27].end 101.63534375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 102.34409375
transcript.pyannote[28].end 109.43159375
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 109.83659375
transcript.pyannote[29].end 116.21534375
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 118.40909375
transcript.pyannote[30].end 133.96784375
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 133.51221875
transcript.pyannote[31].end 142.75971875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 143.40096875
transcript.pyannote[32].end 144.61596875
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 145.22346875
transcript.pyannote[33].end 148.22721875
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 148.41284375
transcript.pyannote[34].end 154.15034375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 151.95659375
transcript.pyannote[35].end 152.02409375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 152.02409375
transcript.pyannote[36].end 152.58096875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 152.58096875
transcript.pyannote[37].end 152.59784375
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 154.50471875
transcript.pyannote[38].end 156.78284375
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 157.99784375
transcript.pyannote[39].end 170.02971875
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 170.02971875
transcript.pyannote[40].end 184.94721875
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 185.09909375
transcript.pyannote[41].end 185.99346875
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 186.29721875
transcript.pyannote[42].end 197.09721875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 197.38409375
transcript.pyannote[43].end 200.38784375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 200.99534375
transcript.pyannote[44].end 243.62159375
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 243.72284375
transcript.pyannote[45].end 252.37971875
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 252.88596875
transcript.pyannote[46].end 253.35846875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 253.56096875
transcript.pyannote[47].end 284.77971875
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 284.77971875
transcript.pyannote[48].end 302.38034375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 301.14846875
transcript.pyannote[49].end 302.29596875
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 302.38034375
transcript.pyannote[50].end 302.73471875
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 302.73471875
transcript.pyannote[51].end 312.64034375
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 312.89346875
transcript.pyannote[52].end 324.84096875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 313.18034375
transcript.pyannote[53].end 313.24784375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 313.26471875
transcript.pyannote[54].end 313.33221875
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 325.27971875
transcript.pyannote[55].end 326.89971875
transcript.pyannote[56].speaker SPEAKER_02
transcript.pyannote[56].start 328.80659375
transcript.pyannote[56].end 330.44346875
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 330.71346875
transcript.pyannote[57].end 342.54284375
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 342.62721875
transcript.pyannote[58].end 350.94659375
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 351.38534375
transcript.pyannote[59].end 358.65846875
transcript.pyannote[60].speaker SPEAKER_02
transcript.pyannote[60].start 358.97909375
transcript.pyannote[60].end 359.90721875
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 361.02096875
transcript.pyannote[61].end 361.78034375
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 362.20221875
transcript.pyannote[62].end 364.24409375
transcript.pyannote[63].speaker SPEAKER_02
transcript.pyannote[63].start 364.71659375
transcript.pyannote[63].end 366.10034375
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 366.45471875
transcript.pyannote[64].end 370.69034375
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 371.28096875
transcript.pyannote[65].end 371.97284375
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 372.52971875
transcript.pyannote[66].end 372.86721875
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 373.30596875
transcript.pyannote[67].end 374.92596875
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 375.34784375
transcript.pyannote[68].end 392.69534375
transcript.pyannote[69].speaker SPEAKER_02
transcript.pyannote[69].start 393.23534375
transcript.pyannote[69].end 394.51784375
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 394.95659375
transcript.pyannote[70].end 396.01971875
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 397.01534375
transcript.pyannote[71].end 400.33971875
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 401.03159375
transcript.pyannote[72].end 404.44034375
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 404.74409375
transcript.pyannote[73].end 407.08971875
transcript.pyannote[74].speaker SPEAKER_02
transcript.pyannote[74].start 407.41034375
transcript.pyannote[74].end 412.47284375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 412.47284375
transcript.pyannote[75].end 412.70909375
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 412.64159375
transcript.pyannote[76].end 416.53971875
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 416.97846875
transcript.pyannote[77].end 420.31971875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 421.16346875
transcript.pyannote[78].end 422.41221875
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 423.12096875
transcript.pyannote[79].end 424.04909375
transcript.pyannote[80].speaker SPEAKER_02
transcript.pyannote[80].start 424.47096875
transcript.pyannote[80].end 425.36534375
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 425.61846875
transcript.pyannote[81].end 433.43159375
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 433.49909375
transcript.pyannote[82].end 437.39721875
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 438.05534375
transcript.pyannote[83].end 439.67534375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 440.43471875
transcript.pyannote[84].end 447.57284375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 448.34909375
transcript.pyannote[85].end 448.36596875
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 448.36596875
transcript.pyannote[86].end 448.43346875
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 448.43346875
transcript.pyannote[87].end 448.77096875
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 448.77096875
transcript.pyannote[88].end 448.80471875
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 448.80471875
transcript.pyannote[89].end 448.87221875
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 448.87221875
transcript.pyannote[90].end 456.63471875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 456.87096875
transcript.pyannote[91].end 457.10721875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 457.10721875
transcript.pyannote[92].end 457.42784375
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 457.42784375
transcript.pyannote[93].end 478.26846875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 476.66534375
transcript.pyannote[94].end 479.38221875
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 480.22596875
transcript.pyannote[95].end 482.75721875
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 482.87534375
transcript.pyannote[96].end 487.70159375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 488.27534375
transcript.pyannote[97].end 498.43409375
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 499.12596875
transcript.pyannote[98].end 499.88534375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 500.18909375
transcript.pyannote[99].end 512.54159375
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 512.72721875
transcript.pyannote[100].end 513.18284375
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 514.09409375
transcript.pyannote[101].end 514.98846875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 516.86159375
transcript.pyannote[102].end 517.16534375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 518.27909375
transcript.pyannote[103].end 519.32534375
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 519.69659375
transcript.pyannote[104].end 521.24909375
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 521.87346875
transcript.pyannote[105].end 523.34159375
transcript.whisperx[0].start 0.401
transcript.whisperx[0].end 1.281
transcript.whisperx[0].text 謝謝謝謝主席 謝謝召委然後請部長處委員好部長辛苦了我看你接任到現在都看
transcript.whisperx[1].start 24.912
transcript.whisperx[1].end 38.788
transcript.whisperx[1].text 都是靠藥物 沒有啦靠藥物在撐 沒有啦都靠腎上腺素啦來 我要跟你感謝這個是東港
transcript.whisperx[2].start 43.462
transcript.whisperx[2].end 55.672
transcript.whisperx[2].text 還有我們南部海邊我們漁船上的漁工不管是近海的不管是遠洋的那以前他們漁工到岸上來整理一些漁獲就被抓
transcript.whisperx[3].start 56.943
transcript.whisperx[3].end 83.94
transcript.whisperx[3].text 那後來在我還有勞動部還有漁業署的努力那終於各位看到漁船博港的時候協助卸貨、整理漁貨、整理漁具補給所需的就是可以接受、可以做你覺得這件事有多嚴重漁船在岸上,本來喔那些漁工站在船上
transcript.whisperx[4].start 85.194
transcript.whisperx[4].end 93.23
transcript.whisperx[4].text 在那邊看台灣人或是老船長、老夫婦在那邊整理魚那些魚公主站在船上看
transcript.whisperx[5].start 94.229
transcript.whisperx[5].end 99.093
transcript.whisperx[5].text 騎公車看外面的攝影台這樣啦看他做事 他們站在那邊看因為他們上岸 就被抓說不能殺魚 不能殺我跟部長報告那魚都死了 都動起來了那不是殺生 我的答案就是殺生啊 殺魚啊死了就整理魚貨而已啊 對不對
transcript.whisperx[6].start 118.444
transcript.whisperx[6].end 144.311
transcript.whisperx[6].text 那個所以其實我們很多外籍漁工其實非常辛苦的啦那當然怎麼樣讓大家的這個相關的規定能夠跟現場的狀況然後工作現場的狀況能夠來去做互相的協調所以每個船長都被划到都快要受不了啦好在有反應然後一直積極的老東部這邊後來也跟那個那個約署
transcript.whisperx[7].start 145.952
transcript.whisperx[7].end 173.054
transcript.whisperx[7].text 這是順義民情我覺得這個是非常非常棒的所以要跟你們加油謝謝蘇貞好那再來講講比較這個巴斯亞表我們通過了兩三個月了那你現在你到底是要再怎麼做你上次有跟我解釋嘛你再解釋一下讓我們大家了解好跟蘇貞還有其實很多關心的朋友說明
transcript.whisperx[8].start 174.815
transcript.whisperx[8].end 199.829
transcript.whisperx[8].text 因為這個是立法院三讀通過的法律修正案當然我們就會來執行那現在勞動部現在在做的事情是必須全力的來規劃配套那這個配套裡面最重要的事情是怎麼樣保障重症家庭的權利因為其實現在我們已經在很多地方聽聞到有些重症家庭他們的這個聘僱的看護移工其實已經有一點想要這個
transcript.whisperx[9].start 201.07
transcript.whisperx[9].end 224.343
transcript.whisperx[9].text 之前所謂說棄重則輕的狀況其實已經陸陸續續會出現所以我們要怎麼保護中正家庭權益所以我們目前其實會設計一個雙軌的程序這個雙軌的程序讓中正家庭可以在這裡面得到比較多的協助跟比較多的方便那因為這個程序的重新設計所以它會深設到其實會需要蠻多增加的人力
transcript.whisperx[10].start 225.143
transcript.whisperx[10].end 240.082
transcript.whisperx[10].text 那這個人力從經費的尋找到招募甚至人力還需要訓練這都需要一些時間 需要幾個月的時間那也包括我們其實也要到這個移工的萊爾姆國來跟他們討論能不能夠增加引進的數量
transcript.whisperx[11].start 241.283
transcript.whisperx[11].end 268.553
transcript.whisperx[11].text 那這個數量的增加那才比較能夠去因應現在可能市場大幅會很快速會增加的這樣的需求避免更大程度的市場供需的失衡所以這整體來說我們都在很審慎而且很積極的作業之中而且跟衛福部也持續的開會討論共同研商那我們評估下來這些工作算起來可能真的還是要個半年六個月
transcript.whisperx[12].start 269.193
transcript.whisperx[12].end 284.234
transcript.whisperx[12].text 那這真的不是我們刻意去做什麼行政怠惰 行政杯葛 都不是我們是要付 某個部分我們是要負起降低衝擊的責任不然如果貿然的沒有把配套做好 狀況開放真的會對中正家庭產生很多的衝擊
transcript.whisperx[13].start 284.955
transcript.whisperx[13].end 312.267
transcript.whisperx[13].text 好 這個部長說的就是我們兩個重點第一個重點就是這個外籍康復制裁他有大時間後他就可以申請他要轉僱主了嘛所以他會對這個當政的重症的他不喜歡招呼他去他要轉換僱主這個是人性啦這是第一個考量第二個考量就是真的外籍康復康復工如果比較素質比較好一點的韓國日本搶著要
transcript.whisperx[14].start 313.348
transcript.whisperx[14].end 325.842
transcript.whisperx[14].text 我們能不能搶得到我們的薪資比他們低老實講還是比較偏低所以這兩個考量那你要做好的配套這個我可以接受那再來你跟我說兩分鐘
transcript.whisperx[15].start 329.2
transcript.whisperx[15].end 343.95
transcript.whisperx[15].text 這個是外籍遺失聯的剛剛盧憲宇委員在講的事情我要跟他follow一下因為外籍的移工勞工第一批要去接到我們的原住民的工作機會
transcript.whisperx[16].start 345.219
transcript.whisperx[16].end 370.221
transcript.whisperx[16].text 那我講一個事實給你看因為原住民這邊我常常在跑屏東那邊就非常熟跟那邊也很綿密每天早上五點多就會看到泰伍啦 春日啦 萊義啦就一個班長然後開一步想要吃 店館在才會有六個七個 八個就下去到北地 還是去到高雄市去做工地 做鐵工
transcript.whisperx[17].start 373.383
transcript.whisperx[17].end 395.731
transcript.whisperx[17].text 那我這邊要我很感謝常說一萬多個人的工作機會會被外國勞工搶走我倒是建議勞動部這邊要加強要去執訓的最當然你要把那個我們原住民的朋友因為都分享體狀的你要讓他的技術水平往上拉你也讓他去騎車你要教他拔車你要讓他騎摩托車你要叫他點摩托車
transcript.whisperx[18].start 401.109
transcript.whisperx[18].end 414.352
transcript.whisperx[18].text 你騎車一天的薪水差不多一千六千八如果電磨棒的都兩千五二千六、兩千八馬上可以增加而且讓它技術水平往上拉你給它砌磚你給它做頭緒一天三千幾塊你給它調整什麼沒意思嘛那個是
transcript.whisperx[19].start 423.173
transcript.whisperx[19].end 447.306
transcript.whisperx[19].text 外籍的勞工進來我在台數六、七還看到外籍的移工連在焊接他們也接受好的訓練之後焊接他們的管線不銹鋼的管線那一天三千幾個所以你要把原住民這裡如果有人說話我頭先保溫後面保溫你一定要自己提升
transcript.whisperx[20].start 448.536
transcript.whisperx[20].end 476.03
transcript.whisperx[20].text 這第二組啦跟文說明確實現在我們看到在整體的產業討論缺工的狀況裡面最缺的就是這些技術工沒錯那這些技術工所以不管是對我想也不只對原住民但對原住民朋友我們其實可以特別怎麼樣子來協助大家做這些職業訓練讓大家在這個技術工的缺乏的狀況之下有機會可以有更好的工作的機會包括更多的收入我想這當然都是我想勞工部很樂意
transcript.whisperx[21].start 478.071
transcript.whisperx[21].end 497.338
transcript.whisperx[21].text 這個要加強一定要more attention在這一塊因為我們原住民很多朋友都當軍警我在大五雲區看到跳傘的大五雲區那整個裡面的幹部不管是軍官士官士兵原住民的朋友佔了56%還是一樣啊
transcript.whisperx[22].start 500.319
transcript.whisperx[22].end 514.805
transcript.whisperx[22].text 所以我覺得我們骨幹都在這裡所以再來就是他們勞力這一塊階級的你一定要幫他訓練讓他們拉高他的資助水平 增加他的收入這個很重要那時間到了喔