IVOD_ID |
149337 |
IVOD_URL |
https://ivod.ly.gov.tw/Play/Clip/1M/149337 |
日期 |
2024-03-06 |
會議資料.會議代碼 |
委員會-11-1-36-3 |
會議資料.會議代碼:str |
第11屆第1會期司法及法制委員會第3次全體委員會議 |
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 |
委員會 |
會議資料.委員會代碼[0] |
36 |
會議資料.委員會代碼:str[0] |
司法及法制委員會 |
會議資料.標題 |
第11屆第1會期司法及法制委員會第3次全體委員會議 |
影片種類 |
Clip |
開始時間 |
2024-03-06T09:44:04+08:00 |
結束時間 |
2024-03-06T09:54:56+08:00 |
影片長度 |
00:10:52 |
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/aa454a369d2b172f3c5ea7b1a0af76153ce99dc43694a3e0f8ba9b0039caa7a6c1dff94e1de332545ea18f28b6918d91.mp4/playlist.m3u8 |
委員名稱 |
謝龍介 |
委員發言時間 |
09:44:04 - 09:54:56 |
會議時間 |
2024-03-06T09:00:00+08:00 |
會議名稱 |
立法院第11屆第1會期司法及法制委員會第3次全體委員會議(事由:邀請行政院人事行政總處人事長列席報告業務概況及立法計畫,並備質詢。) |
gazette.lineno |
264 |
gazette.blocks[0][0] |
謝委員龍介:(9時44分)人事長你好。聽你台語說得不錯,你的口音好像我們南部的。 |
gazette.blocks[1][0] |
蘇人事長俊榮:同鄉的。 |
gazette.blocks[2][0] |
謝委員龍介:是這樣喔!你讀哪間學校?你都把我打聽得這麼清楚!你今天的報告裡面就提到了「當增則增、當減則減」,精神很好!不過,在那天司法院的報告裡面,有一部份本席是支持的,但是有一部分我不認同,為什麼?112年本來提到立法院的就是檢察官助理這件事情,聽起來好像所有的委員都滿贊成的,因為詐騙很多,大家針對這個所以希望能夠提供幫助來偵辦犯罪,結果案子沒送出來啊!今年又拿出了高等法院的案子,讓我實在想不透,所以我那天跟司法院秘書長說,你們這是想要偷渡嘛!利用大家在支持檢察官,其實檢事官已經缺額都沒補足了,缺額達到25%,就是檢事官的部分,然後還要增加檢察官助理,本席認為,這可能是要因應網路犯罪,需要一些新的概念,因此,高等法院司法事務官也是要做舉證等等的工作,所以以你的專業,你有支持這種看法嗎?我是說高等法院的部分。 |
gazette.blocks[3][0] |
蘇人事長俊榮:高等法院的部分,說真的,因為他們要增加的員額、要做什麼工作等等的資料還沒報過來。 |
gazette.blocks[4][0] |
謝委員龍介:禮拜一的報告裡面就有了,照理他來這裡報告之後,因為這攸關人事,所以你應該要很快就收到才對啊! |
gazette.blocks[5][0] |
蘇人事長俊榮:我初步向委員報告一下,委員剛才有表達你的看法,我就不方便再說了,那就是法院組織法,若你要增加檢察官助理的人數,就要動到法院組織法,而法院組織法就是司法院主管、負責的。 |
gazette.blocks[6][0] |
謝委員龍介:本來立法院是滿支持的,就是檢察事務官,理由十分充足,可是他沒有送過來,他也沒做,他就把它留中不發,然後東想想西想想,高等法院那邊也順便給它提出來,既然是在今年、現在提出來,大概就是想要一起來處理,這是司馬昭之心啦!不過站在人事的立場,有必要嗎?應該支持的就應該支持,沒那個必要,為什麼硬要處理?你知道地方辦案的檢察官、檢事官,包括現在說的檢察官助理,那麼多詐騙的案件,但司法院都輕判了,判2年以上的,幾乎是很少,案件那麼多,全部都輕判,然後詐騙的一堆人,這些詐騙案件最後輕判的結果,就是再犯率很高,甚至有的連第一次都沒有被關,當然法官會說這些都是車手,既然都要輕判了,高等法院增加這些人力要幹什麼?有什麼意義?以你的專業,你跟我說明一下。 |
gazette.blocks[7][0] |
蘇人事長俊榮:我跟委員報告,因為委員說了一個很重要的事情,就是檢察體系跟司法體系他們裁判的判決,有時候跟我們的期待會有一些落差,因為我有很多檢察官的朋友…… |
gazette.blocks[8][0] |
謝委員龍介:這不是在說判決,他偵查起訴,當然最後的判決是法官在決定。 |
gazette.blocks[9][0] |
蘇人事長俊榮:是。 |
gazette.blocks[10][0] |
謝委員龍介:現在檢事官的缺額差不多27%,所有一千三百多個檢察官中,缺額也差不多七、八十個…… |
gazette.blocks[11][0] |
蘇人事長俊榮:169…… |
gazette.blocks[12][0] |
謝委員龍介:你說的是檢事官,我剛才跟你說的是檢察官,差不多有近百個,檢事官的缺額達到27.6%,是什麼原因呢?其實他的薪水不錯啊!我看1個月有8萬8,000,為什麼還會補不足? |
gazette.blocks[13][0] |
蘇人事長俊榮:我跟委員報告一下…… |
gazette.blocks[14][0] |
謝委員龍介:是勞逸不均嗎? |
gazette.blocks[15][0] |
蘇人事長俊榮:檢事官現在的問題我覺得是有改善的機會,因為他們的那個訓練場所1年可以訓練多少人是固定的,而他們的訓練是9個月,檢察事務官要訓練9個月才能夠用…… |
gazette.blocks[16][0] |
謝委員龍介:這樣要怎麼樣克服? |
gazette.blocks[17][0] |
蘇人事長俊榮:去找一個空間比較大的嘛! |
gazette.blocks[18][0] |
謝委員龍介:怎麼克服啊? |
gazette.blocks[19][0] |
蘇人事長俊榮:找一個空間,假設現在是90個容訓量,去找一個200個容訓量的場所,然後儘快補人啊,因為現在是…… |
gazette.blocks[20][0] |
謝委員龍介:他們為什麼不找? |
gazette.blocks[21][0] |
蘇人事長俊榮:我不知道,法務部那邊有其他的考慮吧。 |
gazette.blocks[22][0] |
謝委員龍介:你有辦法協助他們嗎?你找一個協助的辦法給本席,本席來替你執行。 |
gazette.blocks[23][0] |
蘇人事長俊榮:我提供一些資料給委員啦! |
gazette.blocks[24][0] |
謝委員龍介:好不好? |
gazette.blocks[25][0] |
蘇人事長俊榮:我提供一些資料給委員。 |
gazette.blocks[26][0] |
謝委員龍介:不是啦,本末倒置嘛! |
gazette.blocks[27][0] |
蘇人事長俊榮:他們現在是有缺啦,但是…… |
gazette.blocks[28][0] |
謝委員龍介:當然有缺啊,但是沒人啊,是什麼原因呢?這應該不是薪水的問題,因為薪水不錯啊! |
gazette.blocks[29][0] |
蘇人事長俊榮:8萬多…… |
gazette.blocks[30][0] |
謝委員龍介:8萬8啊!好啦。 |
gazette.blocks[30][1] |
年改6年了,在年改6年以後,現在一堆軍公教退休的人,你們曾說過5年要調整、檢討一次,去年檢討的結果是怎樣? |
gazette.blocks[31][0] |
蘇人事長俊榮:今年會檢討,因為這件事情…… |
gazette.blocks[32][0] |
謝委員龍介:維持現狀嗎?對不對? |
gazette.blocks[33][0] |
蘇人事長俊榮:沒有,現在銓敘部有在做整體的檢討啦。 |
gazette.blocks[34][0] |
謝委員龍介:退休的部分,從2017年開始,原本差不多3%多,現在降到差不多1.8 %,機關裡面都老化了,學校的老師都高齡化了,為什麼?因為沒有保障嘛,他們覺得退休沒保障嘛,他的退休金跟現在的退休制度沒辦法讓他養老,所以大家都要做到65歲啊,尤其是地方政府,我所在的城市、你的故鄉臺南就是這樣,大家都要做到65歲,所以機關就失去活力了,你對這個有什麼看法?有什麼方法可以改善嗎? |
gazette.blocks[35][0] |
蘇人事長俊榮:有關這個部分,目前我們針對退休的公務同仁是會每4年檢討一次,或者是消費者物價指數超過5%的時候就會去檢討啦,這樣多多少少能夠舒緩一下,但是有一個很重要的概念我跟委員報告一下,因為現在少子化,要進來公務機關的人會比較少,那些人比較慢離開,其實對經驗的傳承還是有幫助的啦。 |
gazette.blocks[36][0] |
謝委員龍介:你跟我講的相反了,之所以會比較少是因為前面沒人退,開出來的缺就越來越少了,而不是要進來的比較少啦,另外一種少就是因為退休沒有保障啦,所以大家進來當公務人員不像以前那麼「加額」了,你應該要針對本質來說明,而不是講表面的,枉費你跟我說你跟我同鄉!公教人員的調薪有沒有黑箱?你覺得呢? |
gazette.blocks[37][0] |
蘇人事長俊榮:絕對沒有黑箱。 |
gazette.blocks[38][0] |
謝委員龍介:沒有黑箱? |
gazette.blocks[39][0] |
蘇人事長俊榮:現在是民主時代,哪有可能有黑箱? |
gazette.blocks[40][0] |
謝委員龍介:專業加給有沒有黑箱? |
gazette.blocks[41][0] |
蘇人事長俊榮:專業加給就是24種,都要公開出來啊! |
gazette.blocks[42][0] |
謝委員龍介:公務人員有6.25%,也有12.79%,請問這是怎麼樣?這是誰在決定的?低高標是誰在處理的? |
gazette.blocks[43][0] |
蘇人事長俊榮:跟委員報告,那是一種誤解啦,那是在調整過程中有些數字呈現出來會有一些誤差範圍啦。 |
gazette.blocks[44][0] |
謝委員龍介:我最後跟你說,有關性別平等工作法,公務人員跟一般企業不同,雖然說公務人員、教育人員、軍職人員同樣也適用,但是第33條、第34條、第38條跟第38條之1不在此限啦,這讓公務人員受到很多委屈,受委屈的人沒辦法申訴,你要怎麼解決? |
gazette.blocks[45][0] |
蘇人事長俊榮:這個部分我們有跟外部的,包括教育部、衛福部及保訓會,事實上有在溝通協調。 |
gazette.blocks[46][0] |
謝委員龍介:他們現在受到性騷擾時要怎麼處理?申訴的管道很少啊! |
gazette.blocks[47][0] |
蘇人事長俊榮:不會啦!不會啦! |
gazette.blocks[48][0] |
謝委員龍介:這個部分請你給本席一個書面說明,好不好? |
gazette.blocks[49][0] |
蘇人事長俊榮:好。 |
gazette.blocks[50][0] |
主席:謝謝龍介委員。 |
gazette.blocks[50][1] |
接下來請莊瑞雄委員發言。 |
gazette.agenda.page_end |
124 |
gazette.agenda.meet_id |
委員會-11-1-36-3 |
gazette.agenda.speakers[0] |
吳宗憲 |
gazette.agenda.speakers[1] |
黃國昌 |
gazette.agenda.speakers[2] |
陳俊宇 |
gazette.agenda.speakers[3] |
沈發惠 |
gazette.agenda.speakers[4] |
謝龍介 |
gazette.agenda.speakers[5] |
莊瑞雄 |
gazette.agenda.speakers[6] |
鍾佳濱 |
gazette.agenda.speakers[7] |
吳思瑤 |
gazette.agenda.speakers[8] |
林思銘 |
gazette.agenda.speakers[9] |
傅崐萁 |
gazette.agenda.speakers[10] |
鄭天財Sra Kacaw |
gazette.agenda.speakers[11] |
羅智強 |
gazette.agenda.speakers[12] |
謝衣鳯 |
gazette.agenda.speakers[13] |
翁曉玲 |
gazette.agenda.speakers[14] |
楊瓊瓔 |
gazette.agenda.page_start |
77 |
gazette.agenda.meetingDate[0] |
2024-03-06 |
gazette.agenda.gazette_id |
1130701 |
gazette.agenda.agenda_lcidc_ids[0] |
1130701_00003 |
gazette.agenda.meet_name |
立法院第11屆第1會期司法及法制委員會第3次全體委員會議紀錄 |
gazette.agenda.content |
邀請行政院人事行政總處人事長列席報告業務概況及立法計畫,並備質詢 |
gazette.agenda.agenda_id |
1130701_00002 |
transcript.pyannote[0].speaker |
SPEAKER_01 |
transcript.pyannote[0].start |
0.03096875 |
transcript.pyannote[0].end |
0.97596875 |
transcript.pyannote[1].speaker |
SPEAKER_00 |
transcript.pyannote[1].start |
3.23721875 |
transcript.pyannote[1].end |
4.63784375 |
transcript.pyannote[2].speaker |
SPEAKER_00 |
transcript.pyannote[2].start |
6.49409375 |
transcript.pyannote[2].end |
16.83846875 |
transcript.pyannote[3].speaker |
SPEAKER_00 |
transcript.pyannote[3].start |
16.97346875 |
transcript.pyannote[3].end |
18.98159375 |
transcript.pyannote[4].speaker |
SPEAKER_00 |
transcript.pyannote[4].start |
21.07409375 |
transcript.pyannote[4].end |
25.81596875 |
transcript.pyannote[5].speaker |
SPEAKER_00 |
transcript.pyannote[5].start |
27.87471875 |
transcript.pyannote[5].end |
30.35534375 |
transcript.pyannote[6].speaker |
SPEAKER_00 |
transcript.pyannote[6].start |
31.85721875 |
transcript.pyannote[6].end |
35.48534375 |
transcript.pyannote[7].speaker |
SPEAKER_00 |
transcript.pyannote[7].start |
36.27846875 |
transcript.pyannote[7].end |
37.59471875 |
transcript.pyannote[8].speaker |
SPEAKER_00 |
transcript.pyannote[8].start |
38.10096875 |
transcript.pyannote[8].end |
39.77159375 |
transcript.pyannote[9].speaker |
SPEAKER_00 |
transcript.pyannote[9].start |
40.39596875 |
transcript.pyannote[9].end |
41.67846875 |
transcript.pyannote[10].speaker |
SPEAKER_00 |
transcript.pyannote[10].start |
43.06221875 |
transcript.pyannote[10].end |
44.09159375 |
transcript.pyannote[11].speaker |
SPEAKER_00 |
transcript.pyannote[11].start |
45.37409375 |
transcript.pyannote[11].end |
46.33596875 |
transcript.pyannote[12].speaker |
SPEAKER_00 |
transcript.pyannote[12].start |
47.38221875 |
transcript.pyannote[12].end |
49.32284375 |
transcript.pyannote[13].speaker |
SPEAKER_00 |
transcript.pyannote[13].start |
50.06534375 |
transcript.pyannote[13].end |
54.43596875 |
transcript.pyannote[14].speaker |
SPEAKER_00 |
transcript.pyannote[14].start |
56.93346875 |
transcript.pyannote[14].end |
63.61596875 |
transcript.pyannote[15].speaker |
SPEAKER_00 |
transcript.pyannote[15].start |
64.59471875 |
transcript.pyannote[15].end |
65.23596875 |
transcript.pyannote[16].speaker |
SPEAKER_00 |
transcript.pyannote[16].start |
66.36659375 |
transcript.pyannote[16].end |
70.97346875 |
transcript.pyannote[17].speaker |
SPEAKER_00 |
transcript.pyannote[17].start |
71.83409375 |
transcript.pyannote[17].end |
73.15034375 |
transcript.pyannote[18].speaker |
SPEAKER_00 |
transcript.pyannote[18].start |
73.89284375 |
transcript.pyannote[18].end |
77.55471875 |
transcript.pyannote[19].speaker |
SPEAKER_00 |
transcript.pyannote[19].start |
79.25909375 |
transcript.pyannote[19].end |
81.09846875 |
transcript.pyannote[20].speaker |
SPEAKER_00 |
transcript.pyannote[20].start |
81.77346875 |
transcript.pyannote[20].end |
83.93346875 |
transcript.pyannote[21].speaker |
SPEAKER_00 |
transcript.pyannote[21].start |
85.08096875 |
transcript.pyannote[21].end |
87.61221875 |
transcript.pyannote[22].speaker |
SPEAKER_00 |
transcript.pyannote[22].start |
89.06346875 |
transcript.pyannote[22].end |
93.31596875 |
transcript.pyannote[23].speaker |
SPEAKER_00 |
transcript.pyannote[23].start |
94.96971875 |
transcript.pyannote[23].end |
96.53909375 |
transcript.pyannote[24].speaker |
SPEAKER_00 |
transcript.pyannote[24].start |
96.97784375 |
transcript.pyannote[24].end |
100.77471875 |
transcript.pyannote[25].speaker |
SPEAKER_00 |
transcript.pyannote[25].start |
101.75346875 |
transcript.pyannote[25].end |
102.20909375 |
transcript.pyannote[26].speaker |
SPEAKER_00 |
transcript.pyannote[26].start |
103.60971875 |
transcript.pyannote[26].end |
107.45721875 |
transcript.pyannote[27].speaker |
SPEAKER_00 |
transcript.pyannote[27].start |
108.13221875 |
transcript.pyannote[27].end |
108.52034375 |
transcript.pyannote[28].speaker |
SPEAKER_00 |
transcript.pyannote[28].start |
109.87034375 |
transcript.pyannote[28].end |
112.46909375 |
transcript.pyannote[29].speaker |
SPEAKER_00 |
transcript.pyannote[29].start |
113.21159375 |
transcript.pyannote[29].end |
114.44346875 |
transcript.pyannote[30].speaker |
SPEAKER_00 |
transcript.pyannote[30].start |
116.08034375 |
transcript.pyannote[30].end |
120.65346875 |
transcript.pyannote[31].speaker |
SPEAKER_00 |
transcript.pyannote[31].start |
121.17659375 |
transcript.pyannote[31].end |
123.04971875 |
transcript.pyannote[32].speaker |
SPEAKER_00 |
transcript.pyannote[32].start |
124.07909375 |
transcript.pyannote[32].end |
127.09971875 |
transcript.pyannote[33].speaker |
SPEAKER_00 |
transcript.pyannote[33].start |
127.33596875 |
transcript.pyannote[33].end |
128.01096875 |
transcript.pyannote[34].speaker |
SPEAKER_00 |
transcript.pyannote[34].start |
128.61846875 |
transcript.pyannote[34].end |
129.93471875 |
transcript.pyannote[35].speaker |
SPEAKER_00 |
transcript.pyannote[35].start |
130.37346875 |
transcript.pyannote[35].end |
130.86284375 |
transcript.pyannote[36].speaker |
SPEAKER_00 |
transcript.pyannote[36].start |
131.13284375 |
transcript.pyannote[36].end |
133.10721875 |
transcript.pyannote[37].speaker |
SPEAKER_00 |
transcript.pyannote[37].start |
133.88346875 |
transcript.pyannote[37].end |
134.50784375 |
transcript.pyannote[38].speaker |
SPEAKER_00 |
transcript.pyannote[38].start |
134.89596875 |
transcript.pyannote[38].end |
137.86596875 |
transcript.pyannote[39].speaker |
SPEAKER_00 |
transcript.pyannote[39].start |
138.33846875 |
transcript.pyannote[39].end |
139.82346875 |
transcript.pyannote[40].speaker |
SPEAKER_00 |
transcript.pyannote[40].start |
140.07659375 |
transcript.pyannote[40].end |
141.86534375 |
transcript.pyannote[41].speaker |
SPEAKER_00 |
transcript.pyannote[41].start |
142.37159375 |
transcript.pyannote[41].end |
143.97471875 |
transcript.pyannote[42].speaker |
SPEAKER_01 |
transcript.pyannote[42].start |
144.64971875 |
transcript.pyannote[42].end |
144.95346875 |
transcript.pyannote[43].speaker |
SPEAKER_01 |
transcript.pyannote[43].start |
145.59471875 |
transcript.pyannote[43].end |
154.03221875 |
transcript.pyannote[44].speaker |
SPEAKER_01 |
transcript.pyannote[44].start |
154.28534375 |
transcript.pyannote[44].end |
154.30221875 |
transcript.pyannote[45].speaker |
SPEAKER_00 |
transcript.pyannote[45].start |
154.30221875 |
transcript.pyannote[45].end |
159.33096875 |
transcript.pyannote[46].speaker |
SPEAKER_01 |
transcript.pyannote[46].start |
154.33596875 |
transcript.pyannote[46].end |
154.53846875 |
transcript.pyannote[47].speaker |
SPEAKER_00 |
transcript.pyannote[47].start |
159.85409375 |
transcript.pyannote[47].end |
164.88284375 |
transcript.pyannote[48].speaker |
SPEAKER_01 |
transcript.pyannote[48].start |
160.32659375 |
transcript.pyannote[48].end |
160.79909375 |
transcript.pyannote[49].speaker |
SPEAKER_01 |
transcript.pyannote[49].start |
161.55846875 |
transcript.pyannote[49].end |
161.67659375 |
transcript.pyannote[50].speaker |
SPEAKER_00 |
transcript.pyannote[50].start |
165.74346875 |
transcript.pyannote[50].end |
165.76034375 |
transcript.pyannote[51].speaker |
SPEAKER_01 |
transcript.pyannote[51].start |
165.76034375 |
transcript.pyannote[51].end |
187.56284375 |
transcript.pyannote[52].speaker |
SPEAKER_00 |
transcript.pyannote[52].start |
187.56284375 |
transcript.pyannote[52].end |
189.68909375 |
transcript.pyannote[53].speaker |
SPEAKER_01 |
transcript.pyannote[53].start |
187.57971875 |
transcript.pyannote[53].end |
188.50784375 |
transcript.pyannote[54].speaker |
SPEAKER_01 |
transcript.pyannote[54].start |
190.00971875 |
transcript.pyannote[54].end |
190.02659375 |
transcript.pyannote[55].speaker |
SPEAKER_00 |
transcript.pyannote[55].start |
190.02659375 |
transcript.pyannote[55].end |
194.73471875 |
transcript.pyannote[56].speaker |
SPEAKER_00 |
transcript.pyannote[56].start |
196.35471875 |
transcript.pyannote[56].end |
197.67096875 |
transcript.pyannote[57].speaker |
SPEAKER_00 |
transcript.pyannote[57].start |
199.15596875 |
transcript.pyannote[57].end |
200.57346875 |
transcript.pyannote[58].speaker |
SPEAKER_00 |
transcript.pyannote[58].start |
201.65346875 |
transcript.pyannote[58].end |
202.59846875 |
transcript.pyannote[59].speaker |
SPEAKER_00 |
transcript.pyannote[59].start |
203.47596875 |
transcript.pyannote[59].end |
204.94409375 |
transcript.pyannote[60].speaker |
SPEAKER_00 |
transcript.pyannote[60].start |
206.47971875 |
transcript.pyannote[60].end |
208.82534375 |
transcript.pyannote[61].speaker |
SPEAKER_00 |
transcript.pyannote[61].start |
209.14596875 |
transcript.pyannote[61].end |
214.24221875 |
transcript.pyannote[62].speaker |
SPEAKER_00 |
transcript.pyannote[62].start |
218.00534375 |
transcript.pyannote[62].end |
220.40159375 |
transcript.pyannote[63].speaker |
SPEAKER_00 |
transcript.pyannote[63].start |
221.95409375 |
transcript.pyannote[63].end |
224.73846875 |
transcript.pyannote[64].speaker |
SPEAKER_00 |
transcript.pyannote[64].start |
225.68346875 |
transcript.pyannote[64].end |
226.62846875 |
transcript.pyannote[65].speaker |
SPEAKER_00 |
transcript.pyannote[65].start |
226.96596875 |
transcript.pyannote[65].end |
228.24846875 |
transcript.pyannote[66].speaker |
SPEAKER_00 |
transcript.pyannote[66].start |
228.80534375 |
transcript.pyannote[66].end |
237.47909375 |
transcript.pyannote[67].speaker |
SPEAKER_00 |
transcript.pyannote[67].start |
238.52534375 |
transcript.pyannote[67].end |
241.86659375 |
transcript.pyannote[68].speaker |
SPEAKER_00 |
transcript.pyannote[68].start |
243.62159375 |
transcript.pyannote[68].end |
246.42284375 |
transcript.pyannote[69].speaker |
SPEAKER_00 |
transcript.pyannote[69].start |
248.11034375 |
transcript.pyannote[69].end |
249.32534375 |
transcript.pyannote[70].speaker |
SPEAKER_00 |
transcript.pyannote[70].start |
250.00034375 |
transcript.pyannote[70].end |
251.23221875 |
transcript.pyannote[71].speaker |
SPEAKER_00 |
transcript.pyannote[71].start |
253.02096875 |
transcript.pyannote[71].end |
257.47596875 |
transcript.pyannote[72].speaker |
SPEAKER_00 |
transcript.pyannote[72].start |
258.13409375 |
transcript.pyannote[72].end |
259.45034375 |
transcript.pyannote[73].speaker |
SPEAKER_00 |
transcript.pyannote[73].start |
260.00721875 |
transcript.pyannote[73].end |
261.84659375 |
transcript.pyannote[74].speaker |
SPEAKER_00 |
transcript.pyannote[74].start |
263.26409375 |
transcript.pyannote[74].end |
265.72784375 |
transcript.pyannote[75].speaker |
SPEAKER_00 |
transcript.pyannote[75].start |
267.31409375 |
transcript.pyannote[75].end |
271.29659375 |
transcript.pyannote[76].speaker |
SPEAKER_00 |
transcript.pyannote[76].start |
272.10659375 |
transcript.pyannote[76].end |
277.45596875 |
transcript.pyannote[77].speaker |
SPEAKER_01 |
transcript.pyannote[77].start |
278.70471875 |
transcript.pyannote[77].end |
296.69346875 |
transcript.pyannote[78].speaker |
SPEAKER_00 |
transcript.pyannote[78].start |
295.59659375 |
transcript.pyannote[78].end |
295.95096875 |
transcript.pyannote[79].speaker |
SPEAKER_00 |
transcript.pyannote[79].start |
296.49096875 |
transcript.pyannote[79].end |
302.43096875 |
transcript.pyannote[80].speaker |
SPEAKER_00 |
transcript.pyannote[80].start |
303.07221875 |
transcript.pyannote[80].end |
304.60784375 |
transcript.pyannote[81].speaker |
SPEAKER_00 |
transcript.pyannote[81].start |
306.46409375 |
transcript.pyannote[81].end |
317.04471875 |
transcript.pyannote[82].speaker |
SPEAKER_00 |
transcript.pyannote[82].start |
318.47909375 |
transcript.pyannote[82].end |
323.77784375 |
transcript.pyannote[83].speaker |
SPEAKER_00 |
transcript.pyannote[83].start |
324.92534375 |
transcript.pyannote[83].end |
328.63784375 |
transcript.pyannote[84].speaker |
SPEAKER_00 |
transcript.pyannote[84].start |
329.26221875 |
transcript.pyannote[84].end |
331.38846875 |
transcript.pyannote[85].speaker |
SPEAKER_00 |
transcript.pyannote[85].start |
332.50221875 |
transcript.pyannote[85].end |
335.82659375 |
transcript.pyannote[86].speaker |
SPEAKER_00 |
transcript.pyannote[86].start |
336.33284375 |
transcript.pyannote[86].end |
339.37034375 |
transcript.pyannote[87].speaker |
SPEAKER_00 |
transcript.pyannote[87].start |
340.11284375 |
transcript.pyannote[87].end |
341.41221875 |
transcript.pyannote[88].speaker |
SPEAKER_00 |
transcript.pyannote[88].start |
343.40346875 |
transcript.pyannote[88].end |
344.97284375 |
transcript.pyannote[89].speaker |
SPEAKER_01 |
transcript.pyannote[89].start |
344.97284375 |
transcript.pyannote[89].end |
345.04034375 |
transcript.pyannote[90].speaker |
SPEAKER_01 |
transcript.pyannote[90].start |
345.39471875 |
transcript.pyannote[90].end |
345.41159375 |
transcript.pyannote[91].speaker |
SPEAKER_00 |
transcript.pyannote[91].start |
345.41159375 |
transcript.pyannote[91].end |
345.96846875 |
transcript.pyannote[92].speaker |
SPEAKER_01 |
transcript.pyannote[92].start |
345.96846875 |
transcript.pyannote[92].end |
357.57846875 |
transcript.pyannote[93].speaker |
SPEAKER_01 |
transcript.pyannote[93].start |
357.74721875 |
transcript.pyannote[93].end |
363.11346875 |
transcript.pyannote[94].speaker |
SPEAKER_01 |
transcript.pyannote[94].start |
363.72096875 |
transcript.pyannote[94].end |
370.23471875 |
transcript.pyannote[95].speaker |
SPEAKER_00 |
transcript.pyannote[95].start |
366.11721875 |
transcript.pyannote[95].end |
366.55596875 |
transcript.pyannote[96].speaker |
SPEAKER_00 |
transcript.pyannote[96].start |
367.07909375 |
transcript.pyannote[96].end |
368.14221875 |
transcript.pyannote[97].speaker |
SPEAKER_00 |
transcript.pyannote[97].start |
368.95221875 |
transcript.pyannote[97].end |
369.52596875 |
transcript.pyannote[98].speaker |
SPEAKER_01 |
transcript.pyannote[98].start |
370.58909375 |
transcript.pyannote[98].end |
379.48221875 |
transcript.pyannote[99].speaker |
SPEAKER_00 |
transcript.pyannote[99].start |
378.23346875 |
transcript.pyannote[99].end |
379.00971875 |
transcript.pyannote[100].speaker |
SPEAKER_01 |
transcript.pyannote[100].start |
379.95471875 |
transcript.pyannote[100].end |
384.69659375 |
transcript.pyannote[101].speaker |
SPEAKER_00 |
transcript.pyannote[101].start |
384.69659375 |
transcript.pyannote[101].end |
384.71346875 |
transcript.pyannote[102].speaker |
SPEAKER_01 |
transcript.pyannote[102].start |
386.68784375 |
transcript.pyannote[102].end |
386.72159375 |
transcript.pyannote[103].speaker |
SPEAKER_00 |
transcript.pyannote[103].start |
386.72159375 |
transcript.pyannote[103].end |
387.98721875 |
transcript.pyannote[104].speaker |
SPEAKER_00 |
transcript.pyannote[104].start |
389.01659375 |
transcript.pyannote[104].end |
392.76284375 |
transcript.pyannote[105].speaker |
SPEAKER_01 |
transcript.pyannote[105].start |
392.76284375 |
transcript.pyannote[105].end |
392.77971875 |
transcript.pyannote[106].speaker |
SPEAKER_00 |
transcript.pyannote[106].start |
394.26471875 |
transcript.pyannote[106].end |
394.28159375 |
transcript.pyannote[107].speaker |
SPEAKER_01 |
transcript.pyannote[107].start |
394.28159375 |
transcript.pyannote[107].end |
399.44534375 |
transcript.pyannote[108].speaker |
SPEAKER_00 |
transcript.pyannote[108].start |
397.16721875 |
transcript.pyannote[108].end |
397.42034375 |
transcript.pyannote[109].speaker |
SPEAKER_00 |
transcript.pyannote[109].start |
398.63534375 |
transcript.pyannote[109].end |
398.93909375 |
transcript.pyannote[110].speaker |
SPEAKER_00 |
transcript.pyannote[110].start |
399.44534375 |
transcript.pyannote[110].end |
399.96846875 |
transcript.pyannote[111].speaker |
SPEAKER_01 |
transcript.pyannote[111].start |
399.96846875 |
transcript.pyannote[111].end |
400.10346875 |
transcript.pyannote[112].speaker |
SPEAKER_01 |
transcript.pyannote[112].start |
400.93034375 |
transcript.pyannote[112].end |
402.02721875 |
transcript.pyannote[113].speaker |
SPEAKER_00 |
transcript.pyannote[113].start |
402.02721875 |
transcript.pyannote[113].end |
409.30034375 |
transcript.pyannote[114].speaker |
SPEAKER_01 |
transcript.pyannote[114].start |
403.00596875 |
transcript.pyannote[114].end |
403.73159375 |
transcript.pyannote[115].speaker |
SPEAKER_00 |
transcript.pyannote[115].start |
409.94159375 |
transcript.pyannote[115].end |
412.03409375 |
transcript.pyannote[116].speaker |
SPEAKER_01 |
transcript.pyannote[116].start |
410.97096875 |
transcript.pyannote[116].end |
411.81471875 |
transcript.pyannote[117].speaker |
SPEAKER_00 |
transcript.pyannote[117].start |
412.97909375 |
transcript.pyannote[117].end |
413.35034375 |
transcript.pyannote[118].speaker |
SPEAKER_00 |
transcript.pyannote[118].start |
415.17284375 |
transcript.pyannote[118].end |
417.82221875 |
transcript.pyannote[119].speaker |
SPEAKER_00 |
transcript.pyannote[119].start |
418.32846875 |
transcript.pyannote[119].end |
420.47159375 |
transcript.pyannote[120].speaker |
SPEAKER_00 |
transcript.pyannote[120].start |
421.29846875 |
transcript.pyannote[120].end |
422.34471875 |
transcript.pyannote[121].speaker |
SPEAKER_00 |
transcript.pyannote[121].start |
423.07034375 |
transcript.pyannote[121].end |
424.80846875 |
transcript.pyannote[122].speaker |
SPEAKER_00 |
transcript.pyannote[122].start |
425.58471875 |
transcript.pyannote[122].end |
427.23846875 |
transcript.pyannote[123].speaker |
SPEAKER_00 |
transcript.pyannote[123].start |
429.73596875 |
transcript.pyannote[123].end |
430.96784375 |
transcript.pyannote[124].speaker |
SPEAKER_01 |
transcript.pyannote[124].start |
430.96784375 |
transcript.pyannote[124].end |
438.46034375 |
transcript.pyannote[125].speaker |
SPEAKER_00 |
transcript.pyannote[125].start |
441.14346875 |
transcript.pyannote[125].end |
442.15596875 |
transcript.pyannote[126].speaker |
SPEAKER_00 |
transcript.pyannote[126].start |
442.57784375 |
transcript.pyannote[126].end |
445.17659375 |
transcript.pyannote[127].speaker |
SPEAKER_00 |
transcript.pyannote[127].start |
445.78409375 |
transcript.pyannote[127].end |
446.59409375 |
transcript.pyannote[128].speaker |
SPEAKER_00 |
transcript.pyannote[128].start |
446.96534375 |
transcript.pyannote[128].end |
449.96909375 |
transcript.pyannote[129].speaker |
SPEAKER_00 |
transcript.pyannote[129].start |
452.07846875 |
transcript.pyannote[129].end |
452.39909375 |
transcript.pyannote[130].speaker |
SPEAKER_00 |
transcript.pyannote[130].start |
454.77846875 |
transcript.pyannote[130].end |
456.46596875 |
transcript.pyannote[131].speaker |
SPEAKER_00 |
transcript.pyannote[131].start |
458.11971875 |
transcript.pyannote[131].end |
460.61721875 |
transcript.pyannote[132].speaker |
SPEAKER_00 |
transcript.pyannote[132].start |
462.27096875 |
transcript.pyannote[132].end |
462.89534375 |
transcript.pyannote[133].speaker |
SPEAKER_00 |
transcript.pyannote[133].start |
463.58721875 |
transcript.pyannote[133].end |
466.05096875 |
transcript.pyannote[134].speaker |
SPEAKER_00 |
transcript.pyannote[134].start |
466.82721875 |
transcript.pyannote[134].end |
470.55659375 |
transcript.pyannote[135].speaker |
SPEAKER_00 |
transcript.pyannote[135].start |
471.65346875 |
transcript.pyannote[135].end |
472.80096875 |
transcript.pyannote[136].speaker |
SPEAKER_00 |
transcript.pyannote[136].start |
474.77534375 |
transcript.pyannote[136].end |
476.41221875 |
transcript.pyannote[137].speaker |
SPEAKER_00 |
transcript.pyannote[137].start |
477.49221875 |
transcript.pyannote[137].end |
478.75784375 |
transcript.pyannote[138].speaker |
SPEAKER_00 |
transcript.pyannote[138].start |
479.93909375 |
transcript.pyannote[138].end |
480.85034375 |
transcript.pyannote[139].speaker |
SPEAKER_00 |
transcript.pyannote[139].start |
481.32284375 |
transcript.pyannote[139].end |
483.28034375 |
transcript.pyannote[140].speaker |
SPEAKER_00 |
transcript.pyannote[140].start |
484.00596875 |
transcript.pyannote[140].end |
484.64721875 |
transcript.pyannote[141].speaker |
SPEAKER_00 |
transcript.pyannote[141].start |
485.15346875 |
transcript.pyannote[141].end |
486.28409375 |
transcript.pyannote[142].speaker |
SPEAKER_00 |
transcript.pyannote[142].start |
487.26284375 |
transcript.pyannote[142].end |
489.86159375 |
transcript.pyannote[143].speaker |
SPEAKER_00 |
transcript.pyannote[143].start |
491.76846875 |
transcript.pyannote[143].end |
494.97471875 |
transcript.pyannote[144].speaker |
SPEAKER_00 |
transcript.pyannote[144].start |
496.72971875 |
transcript.pyannote[144].end |
496.96596875 |
transcript.pyannote[145].speaker |
SPEAKER_01 |
transcript.pyannote[145].start |
496.96596875 |
transcript.pyannote[145].end |
527.03721875 |
transcript.pyannote[146].speaker |
SPEAKER_00 |
transcript.pyannote[146].start |
527.03721875 |
transcript.pyannote[146].end |
527.35784375 |
transcript.pyannote[147].speaker |
SPEAKER_00 |
transcript.pyannote[147].start |
528.23534375 |
transcript.pyannote[147].end |
532.08284375 |
transcript.pyannote[148].speaker |
SPEAKER_00 |
transcript.pyannote[148].start |
533.50034375 |
transcript.pyannote[148].end |
536.90909375 |
transcript.pyannote[149].speaker |
SPEAKER_00 |
transcript.pyannote[149].start |
537.43221875 |
transcript.pyannote[149].end |
537.88784375 |
transcript.pyannote[150].speaker |
SPEAKER_00 |
transcript.pyannote[150].start |
538.34346875 |
transcript.pyannote[150].end |
541.53284375 |
transcript.pyannote[151].speaker |
SPEAKER_00 |
transcript.pyannote[151].start |
542.57909375 |
transcript.pyannote[151].end |
545.70096875 |
transcript.pyannote[152].speaker |
SPEAKER_00 |
transcript.pyannote[152].start |
547.16909375 |
transcript.pyannote[152].end |
552.90659375 |
transcript.pyannote[153].speaker |
SPEAKER_00 |
transcript.pyannote[153].start |
554.03721875 |
transcript.pyannote[153].end |
556.95659375 |
transcript.pyannote[154].speaker |
SPEAKER_00 |
transcript.pyannote[154].start |
558.00284375 |
transcript.pyannote[154].end |
567.21659375 |
transcript.pyannote[155].speaker |
SPEAKER_01 |
transcript.pyannote[155].start |
560.82096875 |
transcript.pyannote[155].end |
561.64784375 |
transcript.pyannote[156].speaker |
SPEAKER_01 |
transcript.pyannote[156].start |
562.06971875 |
transcript.pyannote[156].end |
563.23409375 |
transcript.pyannote[157].speaker |
SPEAKER_01 |
transcript.pyannote[157].start |
563.74034375 |
transcript.pyannote[157].end |
564.22971875 |
transcript.pyannote[158].speaker |
SPEAKER_00 |
transcript.pyannote[158].start |
567.60471875 |
transcript.pyannote[158].end |
567.62159375 |
transcript.pyannote[159].speaker |
SPEAKER_01 |
transcript.pyannote[159].start |
567.62159375 |
transcript.pyannote[159].end |
571.36784375 |
transcript.pyannote[160].speaker |
SPEAKER_00 |
transcript.pyannote[160].start |
571.36784375 |
transcript.pyannote[160].end |
571.41846875 |
transcript.pyannote[161].speaker |
SPEAKER_01 |
transcript.pyannote[161].start |
571.41846875 |
transcript.pyannote[161].end |
571.45221875 |
transcript.pyannote[162].speaker |
SPEAKER_00 |
transcript.pyannote[162].start |
571.45221875 |
transcript.pyannote[162].end |
571.53659375 |
transcript.pyannote[163].speaker |
SPEAKER_01 |
transcript.pyannote[163].start |
571.53659375 |
transcript.pyannote[163].end |
571.57034375 |
transcript.pyannote[164].speaker |
SPEAKER_00 |
transcript.pyannote[164].start |
571.57034375 |
transcript.pyannote[164].end |
574.23659375 |
transcript.pyannote[165].speaker |
SPEAKER_00 |
transcript.pyannote[165].start |
574.35471875 |
transcript.pyannote[165].end |
577.71284375 |
transcript.pyannote[166].speaker |
SPEAKER_00 |
transcript.pyannote[166].start |
578.72534375 |
transcript.pyannote[166].end |
580.41284375 |
transcript.pyannote[167].speaker |
SPEAKER_00 |
transcript.pyannote[167].start |
581.50971875 |
transcript.pyannote[167].end |
582.97784375 |
transcript.pyannote[168].speaker |
SPEAKER_01 |
transcript.pyannote[168].start |
583.41659375 |
transcript.pyannote[168].end |
586.40346875 |
transcript.pyannote[169].speaker |
SPEAKER_00 |
transcript.pyannote[169].start |
586.40346875 |
transcript.pyannote[169].end |
586.67346875 |
transcript.pyannote[170].speaker |
SPEAKER_01 |
transcript.pyannote[170].start |
586.67346875 |
transcript.pyannote[170].end |
597.01784375 |
transcript.pyannote[171].speaker |
SPEAKER_01 |
transcript.pyannote[171].start |
598.16534375 |
transcript.pyannote[171].end |
598.18221875 |
transcript.pyannote[172].speaker |
SPEAKER_00 |
transcript.pyannote[172].start |
598.18221875 |
transcript.pyannote[172].end |
598.51971875 |
transcript.pyannote[173].speaker |
SPEAKER_00 |
transcript.pyannote[173].start |
599.17784375 |
transcript.pyannote[173].end |
601.13534375 |
transcript.pyannote[174].speaker |
SPEAKER_00 |
transcript.pyannote[174].start |
601.92846875 |
transcript.pyannote[174].end |
604.76346875 |
transcript.pyannote[175].speaker |
SPEAKER_00 |
transcript.pyannote[175].start |
605.26971875 |
transcript.pyannote[175].end |
607.69971875 |
transcript.pyannote[176].speaker |
SPEAKER_00 |
transcript.pyannote[176].start |
608.52659375 |
transcript.pyannote[176].end |
609.60659375 |
transcript.pyannote[177].speaker |
SPEAKER_00 |
transcript.pyannote[177].start |
609.92721875 |
transcript.pyannote[177].end |
619.64721875 |
transcript.pyannote[178].speaker |
SPEAKER_00 |
transcript.pyannote[178].start |
620.32221875 |
transcript.pyannote[178].end |
623.68034375 |
transcript.pyannote[179].speaker |
SPEAKER_00 |
transcript.pyannote[179].start |
624.32159375 |
transcript.pyannote[179].end |
625.21596875 |
transcript.pyannote[180].speaker |
SPEAKER_01 |
transcript.pyannote[180].start |
626.95409375 |
transcript.pyannote[180].end |
635.44221875 |
transcript.pyannote[181].speaker |
SPEAKER_01 |
transcript.pyannote[181].start |
636.11721875 |
transcript.pyannote[181].end |
640.08284375 |
transcript.pyannote[182].speaker |
SPEAKER_00 |
transcript.pyannote[182].start |
639.34034375 |
transcript.pyannote[182].end |
641.85471875 |
transcript.pyannote[183].speaker |
SPEAKER_00 |
transcript.pyannote[183].start |
642.32721875 |
transcript.pyannote[183].end |
644.14971875 |
transcript.pyannote[184].speaker |
SPEAKER_01 |
transcript.pyannote[184].start |
644.84159375 |
transcript.pyannote[184].end |
645.80346875 |
transcript.pyannote[185].speaker |
SPEAKER_00 |
transcript.pyannote[185].start |
645.26346875 |
transcript.pyannote[185].end |
647.96346875 |
transcript.pyannote[186].speaker |
SPEAKER_01 |
transcript.pyannote[186].start |
647.96346875 |
transcript.pyannote[186].end |
649.26284375 |
transcript.pyannote[187].speaker |
SPEAKER_00 |
transcript.pyannote[187].start |
652.40159375 |
transcript.pyannote[187].end |
652.67159375 |
transcript.whisperx[0].start |
0.089 |
transcript.whisperx[0].end |
0.749 |
transcript.whisperx[0].text |
法定人數不足 |
transcript.whisperx[1].start |
27.972 |
transcript.whisperx[1].end |
54.116 |
transcript.whisperx[1].text |
哇 你都把我哄得這麼清楚啊你今天報告裡面齁就提到說這個當真則真啦當簡則簡啦齁精神真好不如就在那天司法院的報告裡面齁有一部分分析是支持啦但是有一部分我沒認同 為什麼 |
transcript.whisperx[2].start |
56.957 |
transcript.whisperx[2].end |
83.433 |
transcript.whisperx[2].text |
一百一十二年本來提到這個立法院就說檢察官助理這個事情那聽起來其實所有的委員都蠻贊成因為詐騙很多嘛大家針對這個希望我們幫助辦理檢察管罪結果沒想出來啊沒想出來今年再來提一個 |
transcript.whisperx[3].start |
85.131 |
transcript.whisperx[3].end |
107.121 |
transcript.whisperx[3].text |
高等法院 我想都沒有的所以我覺得司法院的秘書長 你們這個就想要愛人了 偷渡嘛利用大家在支持檢察官 其實檢察官 檢察官助理檢視官裡面已經缺額都不足了缺額達到25%啦 檢視官的部分啦 |
transcript.whisperx[4].start |
116.241 |
transcript.whisperx[4].end |
137.235 |
transcript.whisperx[4].text |
要來增加檢察官處理,我本身認為可能因應網路犯罪,所以需要一些新的改良。若然這樣,看你隔天歡迎司法事務官,還要祈請,我認為你個人在專業,你有支持這種看法嗎?我們說隔天歡迎的部分。 |
transcript.whisperx[5].start |
146.124 |
transcript.whisperx[5].end |
153.673 |
transcript.whisperx[5].text |
閣定範圍的部份說真的啦,因為他們要請假,要做什麼的工作,那個資料還沒報過來啦沒有啦,報告有啊嘛,我們那裡的報告就有啊,大衛的報告就有啊大衛來這裡報告之後,我們那裡人事應該你要很快就收集到才對啊 |
transcript.whisperx[6].start |
165.819 |
transcript.whisperx[6].end |
167.821 |
transcript.whisperx[6].text |
本來立法院是蠻支持檢查事務官 |
transcript.whisperx[7].start |
196.397 |
transcript.whisperx[7].end |
224.419 |
transcript.whisperx[7].text |
理由說要衝捉可是他沒有送過來他也沒衝他就把流裝不發啊去想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想想 |
transcript.whisperx[8].start |
226.168 |
transcript.whisperx[8].end |
241.451 |
transcript.whisperx[8].text |
應該支持就應該支持嘛沒有那個必要有什麼硬要處理你敢知道地方辦案檢察官、檢視官包括現在說的檢察官、助理那些詐騙的案件他所有他都侵犯喔判兩年以上的幾乎是有救救喔案件那麼多全部都侵犯 |
transcript.whisperx[9].start |
253.31 |
transcript.whisperx[9].end |
276.942 |
transcript.whisperx[9].text |
那抓詐騙的一堆人那這些詐騙的案件最後侵犯的結果就是再犯率很高嘛甚至有的第一派都沒在關啊啊當然法官說這都車手啊啊既然都這樣都要侵犯了你增加這些人力幹什麼最高法院你整個這裡的人力有什麼意義啊你以你的專業你給我分析講一下 |
transcript.whisperx[10].start |
278.795 |
transcript.whisperx[10].end |
304.007 |
transcript.whisperx[10].text |
我跟委員報告因為委員講一個很重要的就是檢察那些到司法那些他們的裁判的那個判決有時候跟我們的期待會有一些落差啦因為我有很多檢察官的朋友這不是說判決他起訴警察當然最要判決是你我講的判決嘛是 |
transcript.whisperx[11].start |
306.516 |
transcript.whisperx[11].end |
325.723 |
transcript.whisperx[11].text |
你現在檢視官的缺額差不多27%嘛,我們說就是他所有一千三百多個檢察官裡面缺額差不多七八十個啊啊這個檢視官啦齁,檢視官,你說的是檢視官啦有啦,我剛才跟你說檢察官是差不多...哦,幾百個啊齁 |
transcript.whisperx[12].start |
332.574 |
transcript.whisperx[12].end |
334.777 |
transcript.whisperx[12].text |
那檢視官缺額達到27.6 什麼原因? |
transcript.whisperx[13].start |
334.777 |
transcript.whisperx[13].end |
339.263 |
transcript.whisperx[13].text |
欸 他的薪水不錯捏 我看 一個月八萬八捏啊 為什麼還要補不定? |
transcript.whisperx[14].start |
345.475 |
transcript.whisperx[14].end |
357.062 |
transcript.whisperx[14].text |
我委員報告一個因為是勞役不均嗎不是檢視官他現在的一個問題我覺得是有改善的機會因為他那個訓練就算一年過程可以訓練多少人我是覺得因為他那個訓練是高高位啦 |
transcript.whisperx[15].start |
363.989 |
transcript.whisperx[15].end |
371.972 |
transcript.whisperx[15].text |
檢查事務官要訓練9個月才能夠用找一個空間本來現在假設是90個農訓量你去找一個200個農訓量儘快補啊 因為現在是有 我不知道那有法務部那邊有其他的客戶吧你找一個合作的辦法讓本縣來替你執行 |
transcript.whisperx[16].start |
394.652 |
transcript.whisperx[16].end |
421.819 |
transcript.whisperx[16].text |
我提供一些資料給委員我提供一些資料給委員不是啦 本末倒置嘛一定是有虧啦有虧啦當然有虧啊沒有人要寫什麼原因啊這應該不是薪水的問題薪水不錯啊要備完控備完備啊好啦免改六年以後這裡一堆軍公告退休的人那你說五年要 |
transcript.whisperx[17].start |
423.08 |
transcript.whisperx[17].end |
426.802 |
transcript.whisperx[17].text |
條件一遍 檢討一遍嘛 啊 今年檢討的結果是怎樣?幾年到今年會檢討 因為這件事 會期現狀嗎?對不對?沒有 之前專屬部委員會在檢討啦退休齁 在17年 2017年開始啦齁 我還講 原本差不多3% 現在感覺差不多1.8%齁 |
transcript.whisperx[18].start |
455.287 |
transcript.whisperx[18].end |
482.799 |
transcript.whisperx[18].text |
機關內都弄壞了學校的老師都高齡化為什麼?因為沒有保證,他覺得退休沒有保證他的退休金到現在的退休制度沒有發動可以讓他擁有所以大家都要吐到65萬尤其是地方政府我的想法是你的高雄台南就是這樣 |
transcript.whisperx[19].start |
484.062 |
transcript.whisperx[19].end |
486.183 |
transcript.whisperx[19].text |
這部分其實目前我們大概就是針對退休的公務同仁我們會每四年檢討或者他的那個消費者物價值超過5%會去檢討啦,這樣會 |
transcript.whisperx[20].start |
512.43 |
transcript.whisperx[20].end |
525.674 |
transcript.whisperx[20].text |
舒緩一下,但是有一個很重要的概念,我委員報告一下因為現在是少子化,現在要進來公務機關的人會比較少那些人我伴出去的,對經驗的傳承還是有幫助的啦你以為我講到邊緣會比較少是因為前面沒人拿開闊就越來越少啦,不是要進來會比較少啦就是更另外一種少就是因為退休沒有保障啦 |
transcript.whisperx[21].start |
542.605 |
transcript.whisperx[21].end |
556.516 |
transcript.whisperx[21].text |
所以大家變成你不講武林文,不像以前那樣子啦你不就要先對本席講,你剛才講表明的,不然我們兩個你跟我講你跟我共用的公教人員的條心有沒有黑箱 |
transcript.whisperx[22].start |
558.212 |
transcript.whisperx[22].end |
563.498 |
transcript.whisperx[22].text |
專業家族有黑箱嗎?專業家族24宗都外公開出來阿公布另外後6.2%6.25%後12.79%是怎樣?阿這中間誰在決定的? |
transcript.whisperx[23].start |
581.547 |
transcript.whisperx[23].end |
584.549 |
transcript.whisperx[23].text |
我最好跟你說,那個性別平等工作法裡面公務人員及一般企業不一樣 |
transcript.whisperx[24].start |
608.598 |
transcript.whisperx[24].end |
615.046 |
transcript.whisperx[24].text |
就是說,公務領完的、教育領完、軍職的領完,它有哪個適用,但是33條、34條、38跟38之一不在此限,這讓公務領完受很多委屈,受委屈的人它沒辦法,你怎麼解決? |
transcript.whisperx[25].start |
627.474 |
transcript.whisperx[25].end |
648.708 |
transcript.whisperx[25].text |
這部份其實我們有跟外部我們是跟教育部跟衛福部還有保訓會事實上有在溝通協調你現在想到性騷擾他要怎麼處理啊他申訴的管道路照啊不會啦你給他分析一個書面的說明好啦好啦好 |