iVOD / 162661

Field Value
IVOD_ID 162661
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/162661
日期 2025-06-18
會議資料.會議代碼 委員會-11-3-26-17
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17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 17
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17次全體委員會議
影片種類 Clip
開始時間 2025-06-18T13:30:25+08:00
結束時間 2025-06-18T13:41:56+08:00
影片長度 00:11:31
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/5617cf280bc2552ae126d5fc177d7cff242af1fd96f582309be1ababaaa47466e19b09f8f2dd8cbd5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 楊曜
委員發言時間 13:30:25 - 13:41:56
會議時間 2025-06-18T09:00:00+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17次全體委員會議(事由:邀請勞動部部長就「營造友善職場育兒環境,落實照顧不離職政策規劃」進行專題報告,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 5.22846875
transcript.pyannote[0].end 5.27909375
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 9.14346875
transcript.pyannote[1].end 11.11784375
transcript.pyannote[2].speaker SPEAKER_01
transcript.pyannote[2].start 11.52284375
transcript.pyannote[2].end 12.70409375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 19.18409375
transcript.pyannote[3].end 20.73659375
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 21.85034375
transcript.pyannote[4].end 31.95846875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 32.27909375
transcript.pyannote[5].end 43.04534375
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 43.78784375
transcript.pyannote[6].end 45.71159375
transcript.pyannote[7].speaker SPEAKER_01
transcript.pyannote[7].start 46.53846875
transcript.pyannote[7].end 47.11221875
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 47.82096875
transcript.pyannote[8].end 51.88784375
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 52.66409375
transcript.pyannote[9].end 64.99971875
transcript.pyannote[10].speaker SPEAKER_01
transcript.pyannote[10].start 65.60721875
transcript.pyannote[10].end 66.41721875
transcript.pyannote[11].speaker SPEAKER_01
transcript.pyannote[11].start 67.39596875
transcript.pyannote[11].end 70.45034375
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 71.09159375
transcript.pyannote[12].end 81.68909375
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 82.24596875
transcript.pyannote[13].end 84.86159375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 85.55346875
transcript.pyannote[14].end 87.86534375
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 88.72596875
transcript.pyannote[15].end 89.83971875
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 90.36284375
transcript.pyannote[16].end 92.21909375
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 92.77596875
transcript.pyannote[17].end 94.14284375
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 94.68284375
transcript.pyannote[18].end 115.57409375
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 115.94534375
transcript.pyannote[19].end 120.16409375
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 121.22721875
transcript.pyannote[20].end 123.21846875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 124.02846875
transcript.pyannote[21].end 138.52409375
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 138.96284375
transcript.pyannote[22].end 142.72596875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 143.62034375
transcript.pyannote[23].end 144.44721875
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 144.76784375
transcript.pyannote[24].end 145.12221875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 146.28659375
transcript.pyannote[25].end 148.04159375
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 148.69971875
transcript.pyannote[26].end 164.57909375
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 165.79409375
transcript.pyannote[27].end 166.30034375
transcript.pyannote[28].speaker SPEAKER_01
transcript.pyannote[28].start 167.24534375
transcript.pyannote[28].end 169.55721875
transcript.pyannote[29].speaker SPEAKER_01
transcript.pyannote[29].start 170.67096875
transcript.pyannote[29].end 170.73846875
transcript.pyannote[30].speaker SPEAKER_01
transcript.pyannote[30].start 170.95784375
transcript.pyannote[30].end 173.03346875
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 173.42159375
transcript.pyannote[31].end 174.97409375
transcript.pyannote[32].speaker SPEAKER_01
transcript.pyannote[32].start 175.80096875
transcript.pyannote[32].end 189.84096875
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 190.65096875
transcript.pyannote[33].end 196.06784375
transcript.pyannote[34].speaker SPEAKER_01
transcript.pyannote[34].start 196.54034375
transcript.pyannote[34].end 207.37409375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 208.21784375
transcript.pyannote[35].end 212.57159375
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 213.49971875
transcript.pyannote[36].end 219.20346875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 219.77721875
transcript.pyannote[37].end 222.37596875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 222.89909375
transcript.pyannote[38].end 224.02971875
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 224.68784375
transcript.pyannote[39].end 226.02096875
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 226.45971875
transcript.pyannote[40].end 227.60721875
transcript.pyannote[41].speaker SPEAKER_01
transcript.pyannote[41].start 228.28221875
transcript.pyannote[41].end 229.85159375
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 231.31971875
transcript.pyannote[42].end 235.65659375
transcript.pyannote[43].speaker SPEAKER_01
transcript.pyannote[43].start 236.41596875
transcript.pyannote[43].end 237.78284375
transcript.pyannote[44].speaker SPEAKER_01
transcript.pyannote[44].start 238.87971875
transcript.pyannote[44].end 241.10721875
transcript.pyannote[45].speaker SPEAKER_01
transcript.pyannote[45].start 241.36034375
transcript.pyannote[45].end 247.13159375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 248.48159375
transcript.pyannote[46].end 258.45471875
transcript.pyannote[47].speaker SPEAKER_01
transcript.pyannote[47].start 250.23659375
transcript.pyannote[47].end 250.60784375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 258.97784375
transcript.pyannote[48].end 271.31346875
transcript.pyannote[49].speaker SPEAKER_01
transcript.pyannote[49].start 271.36409375
transcript.pyannote[49].end 280.64534375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 280.99971875
transcript.pyannote[50].end 303.05534375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 304.10159375
transcript.pyannote[51].end 310.56471875
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 310.98659375
transcript.pyannote[52].end 311.52659375
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 311.83034375
transcript.pyannote[53].end 321.98909375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 322.57971875
transcript.pyannote[54].end 340.50096875
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 341.22659375
transcript.pyannote[55].end 345.05721875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 345.54659375
transcript.pyannote[56].end 349.02284375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 349.51221875
transcript.pyannote[57].end 353.89971875
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 354.40596875
transcript.pyannote[58].end 354.94596875
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 355.58721875
transcript.pyannote[59].end 356.09346875
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 356.80221875
transcript.pyannote[60].end 358.10159375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 358.81034375
transcript.pyannote[61].end 359.36721875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 359.95784375
transcript.pyannote[62].end 365.56034375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 366.53909375
transcript.pyannote[63].end 367.83846875
transcript.pyannote[64].speaker SPEAKER_01
transcript.pyannote[64].start 368.63159375
transcript.pyannote[64].end 369.82971875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 370.21784375
transcript.pyannote[65].end 374.67284375
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 375.14534375
transcript.pyannote[66].end 376.00596875
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 376.96784375
transcript.pyannote[67].end 378.79034375
transcript.pyannote[68].speaker SPEAKER_01
transcript.pyannote[68].start 378.97596875
transcript.pyannote[68].end 379.36409375
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 379.92096875
transcript.pyannote[69].end 381.30471875
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 381.47346875
transcript.pyannote[70].end 382.23284375
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 382.57034375
transcript.pyannote[71].end 386.04659375
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 386.62034375
transcript.pyannote[72].end 390.60284375
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 391.46346875
transcript.pyannote[73].end 392.98221875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 393.45471875
transcript.pyannote[74].end 396.47534375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 397.25159375
transcript.pyannote[75].end 399.96846875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 400.84596875
transcript.pyannote[76].end 403.61346875
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 404.32221875
transcript.pyannote[77].end 406.39784375
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 406.73534375
transcript.pyannote[78].end 442.61159375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 441.09284375
transcript.pyannote[79].end 442.57784375
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 442.61159375
transcript.pyannote[80].end 444.65346875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 443.42159375
transcript.pyannote[81].end 460.85346875
transcript.pyannote[82].speaker SPEAKER_00
transcript.pyannote[82].start 461.27534375
transcript.pyannote[82].end 468.16034375
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 463.03034375
transcript.pyannote[83].end 463.09784375
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 463.62096875
transcript.pyannote[84].end 464.73471875
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 465.57846875
transcript.pyannote[85].end 466.47284375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 466.74284375
transcript.pyannote[86].end 481.45784375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 481.72784375
transcript.pyannote[87].end 485.81159375
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 486.14909375
transcript.pyannote[88].end 512.64284375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 501.64034375
transcript.pyannote[89].end 501.67409375
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 509.26784375
transcript.pyannote[90].end 510.31409375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 513.60471875
transcript.pyannote[91].end 534.00659375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 534.76596875
transcript.pyannote[92].end 535.18784375
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 535.84596875
transcript.pyannote[93].end 536.33534375
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 536.72346875
transcript.pyannote[94].end 537.31409375
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 537.44909375
transcript.pyannote[95].end 539.32221875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 540.79034375
transcript.pyannote[96].end 542.49471875
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 543.70971875
transcript.pyannote[97].end 545.65034375
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 545.78534375
transcript.pyannote[98].end 548.90721875
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 549.78471875
transcript.pyannote[99].end 550.86471875
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 552.26534375
transcript.pyannote[100].end 554.13846875
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 554.57721875
transcript.pyannote[101].end 560.06159375
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 560.65221875
transcript.pyannote[102].end 561.00659375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 562.00221875
transcript.pyannote[103].end 563.41971875
transcript.pyannote[104].speaker SPEAKER_01
transcript.pyannote[104].start 563.75721875
transcript.pyannote[104].end 569.44409375
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 570.01784375
transcript.pyannote[105].end 576.64971875
transcript.pyannote[106].speaker SPEAKER_01
transcript.pyannote[106].start 577.27409375
transcript.pyannote[106].end 577.94909375
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 578.53971875
transcript.pyannote[107].end 591.73596875
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 592.25909375
transcript.pyannote[108].end 592.78221875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 593.27159375
transcript.pyannote[109].end 594.38534375
transcript.pyannote[110].speaker SPEAKER_01
transcript.pyannote[110].start 595.58346875
transcript.pyannote[110].end 599.26221875
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 599.56596875
transcript.pyannote[111].end 602.23221875
transcript.pyannote[112].speaker SPEAKER_01
transcript.pyannote[112].start 603.80159375
transcript.pyannote[112].end 605.30346875
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 605.80971875
transcript.pyannote[113].end 607.48034375
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 607.54784375
transcript.pyannote[114].end 609.67409375
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 610.43346875
transcript.pyannote[115].end 612.23909375
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 612.84659375
transcript.pyannote[116].end 616.89659375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 617.48721875
transcript.pyannote[117].end 630.02534375
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 627.40971875
transcript.pyannote[118].end 627.67971875
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 628.42221875
transcript.pyannote[119].end 628.59096875
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 628.77659375
transcript.pyannote[120].end 637.23096875
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 633.38346875
transcript.pyannote[121].end 633.63659375
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 636.18471875
transcript.pyannote[122].end 641.44971875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 639.49221875
transcript.pyannote[123].end 649.06034375
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 649.60034375
transcript.pyannote[124].end 659.72534375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 660.06284375
transcript.pyannote[125].end 662.25659375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 662.81346875
transcript.pyannote[126].end 663.74159375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 664.09596875
transcript.pyannote[127].end 668.75346875
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 669.27659375
transcript.pyannote[128].end 677.30909375
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 680.27909375
transcript.pyannote[129].end 682.82721875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 685.00409375
transcript.pyannote[130].end 688.44659375
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 689.18909375
transcript.pyannote[131].end 690.50534375
transcript.whisperx[0].start 9.181
transcript.whisperx[0].end 12.403
transcript.whisperx[0].text 好 謝謝主席 主席請一下洪部長好 再請部長邀委員好部長好欸 確實是這樣子齁 剛剛蘇信泉委員在講我
transcript.whisperx[1].start 27.015
transcript.whisperx[1].end 51.303
transcript.whisperx[1].text 因為我家也有外籍的家庭看護工就是說最給來這件事情還真的是外籍看護工假如在雇主的家裡面生育、生產、生病其實都是雇主的責務責任都會落在雇主這邊
transcript.whisperx[2].start 55.043
transcript.whisperx[2].end 70.011
transcript.whisperx[2].text 這個方向我們是支持的,可是對於受看護的家庭,其實大家都不像蘇英前、趙偉的安太醫院,人力很夠。
transcript.whisperx[3].start 71.158
transcript.whisperx[3].end 93.905
transcript.whisperx[3].text 那家庭看護工是這樣子,原本我家裡就需要一個人來照顧一個老人,或者是必須要受照顧者。等到家庭看護工也生病,或者是生產的時候,我同時要有兩個人力來補充這個缺口。
transcript.whisperx[4].start 96.021
transcript.whisperx[4].end 122.086
transcript.whisperx[4].text 這個很多制度的設計總是沒有辦法應付所有的變化所以我就剛剛聽到很高興趙偉率先講了在醫院裡面他臉醉了來躲一躲這會算是很基於人道精神確實因為他理想背景部長我來
transcript.whisperx[5].start 124.236
transcript.whisperx[5].end 133.679
transcript.whisperx[5].text 問一下根據行政院主席總署2021年的調查勞工因為照顧65歲以上的家屬離職的人數大概2010年大概有將近1500人已經超過要照顧未滿12歲子女的離職人數
transcript.whisperx[6].start 152.555
transcript.whisperx[6].end 174.22
transcript.whisperx[6].text 也就是說高齡化社會可能高齡化加上少子化所以這個數據可能沒有錯那勞工為了要長期照顧然後離職返家不僅讓家庭少了一份經濟來源
transcript.whisperx[7].start 175.871
transcript.whisperx[7].end 185.084
transcript.whisperx[7].text 對於離職的勞工來講他的退休保障也會減少,年資會中斷嘛那雇主呢也會減少一個熟練然後
transcript.whisperx[8].start 190.717
transcript.whisperx[8].end 212.067
transcript.whisperx[8].text 就是在公司的運作上比較選手的員工就是等於各方面來看都是一件不利的事情啦對公司員工跟國家來看都是不利的那根據勞動部2024年雇用管理局
transcript.whisperx[9].start 213.547
transcript.whisperx[9].end 234.303
transcript.whisperx[9].text 工作場所就業平均概況的調查報告指出勞工最近一年有照顧家人需求的比例是28%而最近一年曾經申請家庭照顧假的女性的受僱者只有5.8%男性只有2.4%
transcript.whisperx[10].start 239.683
transcript.whisperx[10].end 246.871
transcript.whisperx[10].text 有照顧需求跟申請家庭照顧價兩者的落差部長覺得原因是什麼
transcript.whisperx[11].start 248.97
transcript.whisperx[11].end 274.37
transcript.whisperx[11].text 家庭照顧價第一個確實有幾個原因第一個當然有些是資產文化的原因那第二個也有一個原因的確是因為家庭照顧價目前是沒有薪資的所以對於員工來說勞工來說他其實對於去申請比較沒有薪資的這個家庭照顧價他的誘因會比較低沒有薪資啊而且他並入市價來計算
transcript.whisperx[12].start 275.931
transcript.whisperx[12].end 302.73
transcript.whisperx[12].text 所以可能反而有的時候就是直接用市價來請了啦我的看法是這樣子有可能那家庭照顧價併入就是無薪嘛然後併入市價來看那剛剛講的那一份報告呢也講說假如說未來法令有新增
transcript.whisperx[13].start 304.144
transcript.whisperx[13].end 320.303
transcript.whisperx[13].text 沒有不擠薪也沒有津貼補助的長期照顧安排假這個跟剛才的照顧假不一樣照顧假大概就是家裡的人發生重大的一支病啦或是接種疫苗
transcript.whisperx[14].start 323.117
transcript.whisperx[14].end 343.674
transcript.whisperx[14].text 預防接種等等因素這個是假是單日的我現在講的是長時間的所以說也是你們的調查報告裡面假如說有長照安排假或是長照留職停薪勞工會申請的比例高於75%
transcript.whisperx[15].start 346.015
transcript.whisperx[15].end 357.54
transcript.whisperx[15].text 這個是你們的報告的書子顯示說縱使我國長照制度設計把長照安排價
transcript.whisperx[16].start 358.854
transcript.whisperx[16].end 374.114
transcript.whisperx[16].text 等等設計為無薪或者沒有補助勞工還是有申請長照假的意願代表有需求那我們邁入超高齡社會以後啊對於長者
transcript.whisperx[17].start 377.231
transcript.whisperx[17].end 399.616
transcript.whisperx[17].text 長者照顧的需求會一直增加我們勞動部這邊有沒有要參考日本建立的介護休業制度就是可以請93天假或者是國內民團倡議的長照安排假勞動部的看法是怎麼樣
transcript.whisperx[18].start 401.145
transcript.whisperx[18].end 417.256
transcript.whisperx[18].text 跟我們說明喔其實針對因為我們今天討論比較多是顧小那我們現在在講的是顧老的部分那顧老部分確實現在會有一個整體的是這個衛福部現在也在研擬所謂的長照3.0
transcript.whisperx[19].start 418.897
transcript.whisperx[19].end 436.669
transcript.whisperx[19].text 希望能夠針對僱老的部分跟我們的整體的照顧制度尤其是長照照顧的僱老的部分再做一個整體的規劃所以我們目前會先針對僱小的部分先來做處理那當然僱老的部分我們會來看衛福部這邊的長照3.0的規劃他們整個這個政策的規劃的架構來需求
transcript.whisperx[20].start 443.793
transcript.whisperx[20].end 460.556
transcript.whisperx[20].text 我們當然願意跟衛福部一起來做這個事情的討論但是這部分會來自因為顧老要不要有假要不要有留庭要不要有什麼等等的這個概念或者他的概念要限縮還是擴大這裡面會來自於我們整個照顧政策的需求
transcript.whisperx[21].start 461.797
transcript.whisperx[21].end 480.924
transcript.whisperx[21].text 對 所以我們其實跟衛福部針對這部分我們有交換意見過可是現在會先看衛福部整體的照顧政策除了長照制度的配合以外其實勞動部這邊要思考的還有勞資雙方怎麼去達到一個平衡
transcript.whisperx[22].start 482.684
transcript.whisperx[22].end 508.594
transcript.whisperx[22].text 跟文說明其實這個政策邏輯應該是會是從兩位服務這邊的長照政策他的需求他必須開始他整體的需求是如何這個需求上面有沒有需要職場上面的這些架或者是留庭的制度去協助銜接這裡面可能我們其實從勞動部角度我們是在是配合需求端再去做相關的研理就像顧曉
transcript.whisperx[23].start 509.614
transcript.whisperx[23].end 511.799
transcript.whisperx[23].text 我們是先看到有需求我們才來做規劃配合
transcript.whisperx[24].start 514.303
transcript.whisperx[24].end 538.993
transcript.whisperx[24].text 因為部長這樣子講我大概知道啦不過我覺得勞動部的政策擬定除了衛福部的長照政策以外你們還是必須要達到勞資雙方到底怎樣取得一個平衡點部長我問最後一個問題
transcript.whisperx[25].start 543.769
transcript.whisperx[25].end 558.359
transcript.whisperx[25].text 就是說日本為了減輕在職的育兒壓力,並且用彈性制度強制義務化為核心,避免因為育兒導致離職。
transcript.whisperx[26].start 562.689
transcript.whisperx[26].end 575.188
transcript.whisperx[26].text 強化制度和職場友善提升實際使用透過修法大概從今年10月起他們會要求所有的企業含中小企業
transcript.whisperx[27].start 579.09
transcript.whisperx[27].end 600.562
transcript.whisperx[27].text 從底下五項 就是在家工作 調整上下班時間 縮短工時每年至少十天的一日有三假以及企業提供托育措施他們就是從十月起會要求所有的企業從這五項裡面
transcript.whisperx[28].start 603.871
transcript.whisperx[28].end 624.611
transcript.whisperx[28].text 最少要實施兩項那我們我們勞動部覺得這個這樣子的政策值不值得我們會不會會不會參考然後推行我想我們我們其實都願意來參考各國的制度甚至也不只是日本但是他就就
transcript.whisperx[29].start 625.371
transcript.whisperx[29].end 642.615
transcript.whisperx[29].text 這五項裡面它其實也包括了育嬰留庭 家庭照顧 其實我們也有現在是說強制的五選二就是強制性的我們的育嬰留庭跟家庭照顧現在在法律上的概念其實也是強制的就是說怎麼減輕在職者的育兒壓力
transcript.whisperx[30].start 649.736
transcript.whisperx[30].end 676.088
transcript.whisperx[30].text 其實算是國家一個很重要的政策因為育兒的環境越不友善少子化的趨勢就會越嚴重還有一些問題今天因為時間的關係我下一次再跟部長做探討謝謝部長 謝謝主席
transcript.whisperx[31].start 680.305
transcript.whisperx[31].end 690.335
transcript.whisperx[31].text 好謝謝謝謝楊耀忍謝謝部長那本日會議巡打全部結束委員林德甫