工時有幾長？貧窮新一代的就業與貧窮報告

近年，社會出現有關年輕人「躺平」的討論，指年輕新一代不願找工作、不願勤奮加班、不規構未來。教育局局長楊潤雄亦曾在網誌撰文表示憂慮，批評「躺平這種消極的人生心態，長遠會窒礙社會的進步」。 不過，根據香港政府統計處2021年收入及工時按年統計調查報告， 2021年5月至6月，15至24歲及25至34歲受訪者每周的工作時數中位數分別為44.3及42小時，比亞洲其他國家要高；而2022年4至6月，20至24歲及25至29歲的勞動人口參與率分別為53.5%及87%，後者更是所有年齡組別中第二高（僅次於30至34歲年齡組別），反映年輕人並沒有不願意長時間工作和就業，與成年人無異。 另外，根據中大亞太研究所於本年四月進行的一項調查，超過半數受訪者認為香港社會並沒有足夠機會與年輕一代向上流動，更有六成半受訪者認為，現時香港向上流動的機會比過去10年要少。 在是次研究中，發現有不少手持大學文憑的畢業生甫踏入社會，便從事三行、保安、飲食業等藍領工種，以體力勞動換取更高薪酬。文職的工作機會雖不算難找，但對於畢業生來說，待遇多不及前者；初入職場的年輕人便要忍受長工時以換取較可觀的薪金，更因長期體力勞動及工作環境惡劣，導致工傷或患上職業病，造成不可逆轉的傷害；選擇白領工作的年輕人則花空餘時間研究創業路向，望有天可擺脫低工資、長OT的工作常態。 年輕人是社會重要的群體，促進社會不同面向的發展和進步。勞工議題，正正就是影響年輕人最深遠的問題。不過，社會一般會把青年遇到的問題視為過渡性現象，隨著他們成長而消失。坊間少有深入討論，以致一般年輕人以為工作的沉重是理所當然，對自身的勞工權益鮮有認識。 上述所提及的年輕人工時長的狀況，窒礙他們在成長階段的探索，因長工時影響反心健康、無法進修、交結朋友、和家人相處及了解自我。工時長等問題在港是老生常談，卻是待解決的重要議題。香港人多年來一直受長工時的困擾，回顧香港的工時政策，卻未見突破。由勞顧會於2018年宣布推出「11個行業工時指引」，距今已4年，仍未見進展。更何況，指引的條文亦不適用於大部份長工時的打工仔女，例如只保障月薪不超過1.1萬元作為界定工資較低的基層僱員的工資線等規定。可見，像過往一樣，政府及商界等對標準工時並不持開放態度。 誠然，參考不同地區及國家的工時政策，香港則顯得相當落後。中國、日本、台灣、韓國及新加坡均有明確法例規管工時，如超時工作的補水機制、每天工作8小時作為標準工時等。如香港政策要推行工時相關的政策，大有參考例子。本報告亦整合及分析了上述地區的工時政策，有助了解其他地區的勞工法例。 是次研究探討了現行的工時政策下香港年輕僱員的工作現況。透過深入訪談及問卷調查，發現長工時與生理、心理、社交及家庭關係的影響，以及就研究結果提倡相應的政策改革，讓社會大眾及年輕人自身了解他們的勞動現況，剖析處境並提出有效的改善方針。https://commons.ln.edu.hk/ccrd_report/1002/thumbnail.jp

最低工資有幾低? 貧窮新一代的就業困境報告

為了解香港青年對就業、貧窮、體面生活、相關政策的看法，以及他們收入和支出的情況，嶺南大學政策研究院、文化研究及發展中心聯合進行一項題為《最低工資有幾低？貧窮新一代的就業困境報告》的調查。結果發現，四成接受深度訪談的青年自認貧窮，而絕大部分已有全職工作的受訪青年認為，最低工資調整幅度太低，自己未能受惠。 嶺大研究團隊從2022年5月至12月，先後透過兩輪深度訪談，訪問了67位18至29歲、收入低於2萬元、有工作經驗的青年。另外，團隊亦透過兩輪問卷調查，分別收集到164份及253份有效回覆。 調查結果發現，絕大部分年輕人覺得自己的工資太低，待遇與工作不相稱。受訪青年的收入來源包括全職工作、兼職工作。深度訪談年輕人的收入中位數為15,200元，而問卷調查的收入中位數結果則是6,000至9,999元。一方面，大部分有全職工作的青年認為自己工時長、部分行業長期低薪，比不上任職其他行業的同輩，而覺得不滿。壓力同時來自高昂的生活成本和遙不可及的人生目標，包括置業。 大約四成接受第二輪深度訪談的青年自認是貧窮，他們對於貧窮有多元化的理解。有青年認為三餐不繼才算得上貧窮，有些人覺得人工未達到港人月入中位數就算是貧窮，亦有人認很多目標未能達成，導致「精神貧窮」。其餘自覺不貧窮的青年部分歸因於家庭支援，可以滿足基本需求以外的消費，例如購物和旅遊。 絕大部分已有全職工作的受訪青年覺得最低工資調整幅度太低，自己未能受惠。無論認為自己屬於中產或基層的受訪者，均有共識，認為即使法定最低工資水平提升至40元依然是太低，與市場脫節，調整幅度不合理。不少人往往將最低工資時薪和「一餐飯」的開支掛鉤，認為最低工資水平要吃得起「一餐飯」才合理。受訪者認為最低工資如有合理升幅及政策檢討，對基層家庭及兼職工作者有很大幫助。 問卷調查結果推算，受訪青年要滿足現時的生活開支水平，時薪應該要達到71.6元。問卷調查的結果顯示青年的個人月均生活支出為16,789元，扣除教育開支，平均每月支出約14,894元，按一個月工作26日，每日8小時計算出時薪水平為71.6元，與目前最低工資水平相距很遠。 研究團隊建議，政府應從多方面著手解決此迫切的社會問題。首先，當局應檢討最低工資政策的定位，使它與其他扶貧政策互相配合，以保障不同需要的群體；第二，當局應透明化最低工資的調整過程，改為「一年一檢」；第三，團隊建議重啟標準工時立法程序，訂明標準工時應為每周40小時，加班工資應為正常工資的1.5倍，每月亦應設有加班和總工時上限，並以此為基礎制定「過勞死」的法律定義，把過勞死定為僱主須按《僱員補償條例》（第282章）作出補償的事故。最後，團隊建議政府主動開展設立失業保障制度的工作，包括探討供款式失業保險、檢討現行失業綜援、遣散費／長期服務金，並重視年輕人對相關政策的意見。https://commons.ln.edu.hk/ccrd_report/1003/thumbnail.jp

Primary Tumor Radiomic Model for Identifying Extrahepatic Metastasis of Hepatocellular Carcinoma Based on Contrast Enhanced Computed Tomography

This study aimed to identify radiomic features of primary tumor and develop a model for indicating extrahepatic metastasis of hepatocellular carcinoma (HCC). Contrast-enhanced computed tomographic (CT) images of 177 HCC cases, including 26 metastatic (MET) and 151 non-metastatic (non-MET), were retrospectively collected and analyzed. For each case, 851 radiomic features, which quantify shape, intensity, texture, and heterogeneity within the segmented volume of the largest HCC tumor in arterial phase, were extracted using Pyradiomics. The dataset was randomly split into training and test sets. Synthetic Minority Oversampling Technique (SMOTE) was performed to augment the training set to 145 MET and 145 non-MET cases. The test set consists of six MET and six non-MET cases. The external validation set is comprised of 20 MET and 25 non-MET cases collected from an independent clinical unit. Logistic regression and support vector machine (SVM) models were identified based on the features selected using the stepwise forward method while the deep convolution neural network, visual geometry group 16 (VGG16), was trained using CT images directly. Grey-level size zone matrix (GLSZM) features constitute four of eight selected predictors of metastasis due to their perceptiveness to the tumor heterogeneity. The radiomic logistic regression model yielded an area under receiver operating characteristic curve (AUROC) of 0.944 on the test set and an AUROC of 0.744 on the external validation set. Logistic regression revealed no significant difference with SVM in the performance and outperformed VGG16 significantly. As extrahepatic metastasis workups, such as chest CT and bone scintigraphy, are standard but exhaustive, radiomic model facilitates a cost-effective method for stratifying HCC patients into eligibility groups of these workups

Development of an individualized risk calculator of treatment resistance in patients with first-episode psychosis (TRipCal) using automated machine learning: a 12-year follow-up study with clozapine prescription as a proxy indicator

Abstract About 15–40% of patients with schizophrenia are treatment resistance (TR) and require clozapine. Identifying individuals who have higher risk of development of TR early in the course of illness is important to provide personalized intervention. A total of 1400 patients with FEP enrolled in the early intervention for psychosis service or receiving the standard psychiatric service between July 1, 1998, and June 30, 2003, for the first time were included. Clozapine prescriptions until June 2015, as a proxy of TR, were obtained. Premorbid information, baseline characteristics, and monthly clinical information were retrieved systematically from the electronic clinical management system (CMS). Training and testing samples were established with random subsampling. An automated machine learning (autoML) approach was used to optimize the ML algorithm and hyperparameters selection to establish four probabilistic classification models (baseline, 12-month, 24-month, and 36-month information) of TR development. This study found 191 FEP patients (13.7%) who had ever been prescribed clozapine over the follow-up periods. The ML pipelines identified with autoML had an area under the receiver operating characteristic curve ranging from 0.676 (baseline information) to 0.774 (36-month information) in predicting future TR. Features of baseline information, including schizophrenia diagnosis and age of onset, and longitudinal clinical information including symptoms variability, relapse, and use of antipsychotics and anticholinergic medications were important predictors and were included in the risk calculator. The risk calculator for future TR development in FEP patients (TRipCal) developed in this study could support the continuous development of data-driven clinical tools to assist personalized interventions to prevent or postpone TR development in the early course of illness and reduce delay in clozapine initiation

Host-response biomarkers for diagnosis of late-onset septicemia and necrotizing enterocolitis in preterm infants

Preterm infants are highly susceptible to life-threatening infections that are clinically difficult to detect, such as late-onset septicemia and necrotizing enterocolitis (NEC). Here, we used a proteomic approach to identify biomarkers for diagnosis of these devastating conditions. In a case-control study comprising 77 sepsis/NEC and 77 nonsepsis cases (10 in each group being monitored longitudinally), plasma samples collected at clinical presentation were assessed in the biomarker discovery and independent validation phases. We validated the discovered biomarkers in a prospective cohort study with 104 consecutively suspected sepsis/NEC episodes. Proapolipoprotein CII (Pro-apoC2) and a des-arginine variant of serum amyloid A (SAA) were identified as the most promising biomarkers. The ApoSAA score computed from plasma apoC2 and SAA concentrations was effective in identifying sepsis/NEC cases in the case-control and cohort studies. Stratification of infants into different risk categories by the ApoSAA score enabled neonatologists to withhold treatment in 45% and enact early stoppage of antibiotics in 16% of nonsepsis infants. The negative predictive value of this antibiotic policy was 100%. The ApoSAA score could potentially allow early and accurate diagnosis of sepsis/NEC. Upon confirmation by further multicenter trials, the score would facilitate rational prescription of antibiotics and target infants who require urgent treatment