從Basay 到金雞貂──臺灣原住民社群關係之性質與變遷

[[abstract]]本文係以北部濱海地區的原住民之社群關係為研究核心，從「地域社群」概念出發，透過歷時性的觀察視角，檢視十七世紀至清代的北濱原住民─指涉的對象分別為十七世紀的Basay 部落，與清代的金包里、大雞籠、三貂三社，於經歷過西荷勢力進駐與納入清朝的帝國體制下，其社群內部結構、對外的村際關係、與外來勢力的互動方面之現象及變遷。藉由文獻、契書、考古資料同時檢視空間與時間的方式，剖析兩個時代的社群所呈現在社會、經濟、文化層面的延續性、相關性、抑或斷裂性，以及社群關係的結構內涵所發生的作用。北部濱海地區做為一個完整的地理區域，從Basay 到金雞貂，係從原始建構在血緣、地緣而發展出具有相當程度文化同質性的社群關係，經歷清朝政治勢力與漢人社會在各方面產生一體兩面的影響下，形成的金雞貂三社社群關係與結構已然改變，無論是空間上的社域分佈，亦或與住民密切相關的生計問題、文化傳統，均顯示與漢人農業型態的文化發生涵化的痕跡。北濱原住民的地理、歷史特殊性，有臺灣島上強烈區域性發展的特質，藉由本文的論述，希望能提供一個可探索的途徑，去瞭解臺灣原住民社群關係的歷史脈絡。

The relation between stigma and acceptance of food product- take chewy starch food as an example

　　本研究探討經過毒澱粉事件後，是否出現對Q彈澱粉食品烙印的現象，而烙印又是如何伴隨著信任度、劑量危害敏感度等因素共同影響接受度呢？本研究假設對產品的烙印是一種負面的心理情感狀態，是風險社會擴大後造成的結果，但烙印會進一步影響利益感知和風險感知，最後再影響民眾對於Q彈澱粉食品的接受度。過往研究中，對風險管理者的信任、食品相關知識、性別、年紀、收入等變項均與風險感知及接受度有顯著關聯，在本研究希望探討烙印是否為預測模型中影響接受度的最主要因素、也想探討劑量危害敏感度與風險管理者之信任是否會影響接受度，最後再提供相關建議。 　　本研究採問卷調查法進行資料收集，針對台灣16到45歲的民眾採取非隨機配額抽樣，用路徑分析探討變項間關聯。 　　在分析714個有效樣本後，發現： 1.受試者的負面烙印偏高、風險感知偏高、對風險管理者的信任度偏低、接受度與利益感知呈現中等沒意見的態度； 2.負面形象烙印程度是影響接受度最主要的因素，與接受度有顯著負相關，負面形象烙印也和風險感知呈現顯著正相關； 3.利益感知是影響接受度第二重要的因素，並與對廠商的信任有顯著關聯； 4.劑量危害敏感度會透過風險感知與風險感知對接受度產生顯著影響； 5.信任度需透過風險感知與利益感知才對接受度產生效果，其中對廠商的信任又比對政府信任更重要。 6.背景變項會影響研究變項，但在偏相關研究中，控制了年紀、月收入、最高學歷後，研究變項之間的關聯依舊顯著。並發現年紀與劑量反應敏感度呈現負相關、年紀和月收入與信任呈現負相關，最高學歷和烙印與劑量危害敏感度有顯著關聯。 　　研究結論，證實烙印和接受度有顯著關聯，並且劑量危害敏感度也是一個重要的影響變項。政府應該推廣劑量危害的相關概念，可以讓民眾更準確地判斷風險大小，避免過度恐慌。在食安事件之後，若媒體與政府可以避免引發負面的情緒、提升產品之利益感知、政府和餐飲業者展現自己對風險控管的能力進而提高民眾對他們的信任度，或是從影響消費者行為之因素介入，還是有機會讓消費者願意接受這類食品。 　　本研究限制是問卷透過網路和紙本同步發放，而問卷發放期間台灣剛好發生食品安全事件，可能無法排除其他食安事件可能的潛在影響，需要未來不同時間點的研究來證實變項間關係穩健性。In 2013, the maleic anhydride (MA) was illegally added into starch to prepare chewy Taiwanese traditional foods. MA may cause adverse effects to kidney of rodents but the effect on human is uncertain. After a series of reports on the MA adulteration appeared on TV and newspapers, the consumers were of great concerns of potential health effects and dissatisfaction toward to governments, and led to dramatic drop in sales of the traditional foods in Taiwan. This study aimed to investigate whether the stigma existed after the MA-tainted starch incident and how stigma affected the acceptance of chewy food with path analysis. Methods and material：In this study, I adopted the questionnaire to collect data associated with the attitudes of study subjects aged from 16 to 45 in Taiwan. I defined stigma as the negative psychological status which was production of social amplification of food risk. In addition, I assumed the stigma would affect the acceptance both directly and indirectly, and risk/ benefit perception would served important mediators between trust in government, trust in food industries, dose-response sensitivity and acceptance of current chewy food. I used several scales from previous studies, namely: the stigma scale revised from Kasperson et al.(2001) and Peters et al.(2004), the risk perception scale from Kirk et al.(2002), the benefit perception scale from Saba and Messina (2003), dose-response sensitivity scales combined Kraus et al.(1994) with Slovic et al.(1995), trust scale from Siegrist et al.(2012), and I also developed the acceptance scale by integrating the consumption intention, behavior and acceptability attitude of chewy starch food. I validated the questionnaire by Cronbach’s alpha, test-retest reliability and factor analysis by SPSS in pretest stage. In this study, 714 subjects were recruited by path analysis using Lisrel to figure out the association in the proposed model. Results：(1) The respondents shown higher level of food stigma, higher perceived risk, lower trust toward risk managers. (2) The stigma had both direct and indirect effect to the chewy food acceptance, and stigma was the most important variable in the model. (3) The benefit perception was the second influential factor to predict the acceptance. (4) Dose-response sensitivity had significant effect on the perceptions and affected acceptance indirectly. (5) Trusts were important in the model but not directly affect the acceptance, and trust in industries was more important than trust toward government. (6) Among the background variables, age has negative relationship with dose-response sensitivity and food acceptance; income and age were significant negative associated with the trust in risk managers; expertise made the stigma level and dose-response seneitivity different. Conclusion：Stigma did appear in Taiwan and had a significant positive correlation to risk perception, negative correlation to benefit perception, and posed a negative effect on chewy food acceptance. Stigma had direct effect to acceptace and would affect risk perception with other variables like the dose-response sensitivity, trust in government and affect acceptance indirectly. Benefit perception was one strong determent which would be affected by the trust in industry. For further application, to emphasize the benefit aspect of foods, to increase the trust toward risk managers, and not to create negative affects may increase the acceptance of foods after food safety incident. Limit：This study cannot exclude the potential effect of the incident of gutter oil and other food incidents. It may need more studies to confirm the model by controlling the time effect

A Study of Applying Public Opinion Mining to Predict the Housing Market Near the Taipei MRT Stations

因網際網路帶來的便利性與即時性，網路新聞成為社會大眾吸收與傳遞新聞資訊的重要管道之一，而累積的巨量新聞亦可反映出社會輿論對某特定新聞議題之即時反應、熱門程度以及情緒走向等。 因此，本研究期望借由意見探勘與情緒分析技術，從特定領域新聞中挖掘出有價值的關聯，並結合傳統機器學習建立一個房地產市場的預測模式，提供購屋決策的參考依據。 本研究搜集99年1月1日至103年6月30日共1,1150筆房地產新聞，以及8,165件捷運週邊250公尺內房屋買賣交易資料，運用意見探勘萃取意見詞彙進行情緒分析，並建立房市情緒與成交價量時間序列，透過半年移動平均、二次移動平均及成長斜率，瞭解社會輿情對房市行情抱持樂觀或悲觀，分析社會情緒與實際房地產成交間關聯性，以期能找出房地產買賣時機點，並進一步結合情緒及房地產的環境影響因素，藉由支援向量機建立站點房市的預測模型。 實證結果中，本研究發現房市情緒與成交價量之波動有一定的週期與相關性，且新捷運開通前一年將連帶影響整體捷運房市波動，當成交線穿越情緒線且斜率同時向上時，可做為適當的房市進場時機點。而本研究針對站點情緒與環境變數所建立之預測模型，其預測新捷運線站點之平均準確率為69.2％，而預測新捷運線熱門站點之準確率為78％，顯示模型於預測熱門站點上具有不錯的預測能力。Nowadays, E-News have become an important way for people to get daily information. These enormous amounts of news could reflect public opinions on a particular attention or sentiment trends in news topics. Therefore, how to use opinion mining and sentiment analysis technology to dig out valuable information from particular news becomes the latest issue. In this study, we collected 1,1150 house news and 8,165 house transaction records around the MRT stations within 250 meters over the last five years. We extracted the emotion words from the news by manipulating opinion mining. Furthermore, we built moving average lines and the slope of the moving average in order to explore the relationship and entry point between public opinion and housing market. In conclusion, we indicated that there is a high correlation between the news sentiment and housing market. We also uses SVM algorithm to construct a model to predict housing hotspots. The results demonstrate that the SVM model reaches average accuracy at 69.2% and the model accuracy increases up to 78% for predicting housing hotspots. Besides, we also provide investors with a basis of entry point into the housing market by utilizing the moving average cross overs and slopes analysis and a better way of predicting housing hotspots

Evaluation of Breast Cancer Service Screening Programme with a Bayesian Approach: Mortality Analysis in a Finnish Region

Evaluation of long-term effectiveness of population-based breast cancer service screening program in a small geographic area may suffer from self- selection bias and small samples. Under a prospective cohort design with exposed and non-exposed groups classified by whether women attended the screen upon invitation, we proposed a Bayesian acyclic graphic model for correcting self-selection bias with or without incorporation of prior information derived from previous studies with an identical screening program in Sweden by chronological order and applied it to an organized breast cancer service screening program in Pirkanmaa center of Finland. The relative mortality rate of breast cancer was 0.27 (95% CI 0.12-0.61) for the exposed group versus the non-exposed group without adjusting for self-selection bias. With adjustment for selection-bias, the adjusted relative mortality rate without using previous data was 0.76 (95% CI 0.49- 1.15), whereas a statistically significant result was achieved [0.73 (95% CI 0.57-0.93)] with incorporation of previous information. With the incorporation of external data sources from Sweden in chronological order, adjusted relative mortality rate was 0. 67 (0.55-0.80). We demonstrated how to apply a Bayesian acyclic graphic model with self-selection bias adjustment to evaluating an organized but non-randomized breast cancer screening program in a small geographic area with a significant 27% mortality reduction that is consistent with the previous result but more precise. Around 33% mortality was estimated by taking previous randomized controlled data from Sweden

Estimation of Natural History Parameters of Breast Cancer Based on Non- Randomized Organized Screening Data: Subsidiary Analysis of Effects of Inter-Screening Interval, Sensitivity, and Attendance Rate on Reduction of Advanced Cancer

Estimating the natural history parameters of breast cancer not only elucidates the disease progression but also make contributions to assessing the impact of inter-screening interval, sensitivity, and attendance rate on reducing advanced breast cancer. We applied three-state and five- state Markov models to data on a two-yearly routine mammography screening in Finland between 1988 and 2000. The mean sojourn time (MST) was computed from estimated transition parameters. Computer simulation was implemented to examine the effect of inter-screening interval, sensitivity, and attendance rate on reducing advanced breast cancers. In three-state model, the MST was 2.02 years, and the sensitivity for detecting preclinical breast cancer was 84.83%. In five-state model, the MST was 2.21 years for localized tumor and 0.82 year for non-localized tumor. Annual, biennial, and triennial screening programs can reduce 53, 37, and 28% of advanced cancer. The effectiveness of intensive screening with poor attendance is the same as that of infrequent screening with high attendance rate. We demonstrated how to estimate the natural history parameters using a service screening program and applied these parameters to assess the impact of inter-screening interval, sensitivity, and attendance rate on reducing advanced cancer. The proposed method makes contribution to further cost-effectiveness analysis. However, these findings had better be validated by using a further long-term follow-up data

以翻轉式概念構圖提升學生閱讀理解能力之研究 The Flip Concept Map in Relation to Student’s Reading Comprehension Skills

本研究以翻轉式概念構圖為教學策略，期望能提升學生的閱讀理解能力。研究對象為新北市某國小五年級學生，以立意取樣選取兩個班級作為實驗組及控制組，實驗組教師運用翻轉式概念構圖進行教學，控制組教師以傳統講述式進行大意教學。本研究採準實驗研究設計，歷時10週，共10堂課（400分鐘），研究結果發現，實驗組經由翻轉式概念構圖的教學，在「提取訊息」與「推論訊息」沒有顯著差異，但在「詮釋整合」與「比較評估」的能力明顯優於控制組，且實驗組之中的高學習成效學生經過實驗後，在「推論訊息」能力上與低學習成效學生沒有顯著差異，但在「提取訊息」、「詮釋整合」及「比較評估」的能力優於低學習成效的學生。因此，翻轉式概念構圖教學策略能有效提升學生的閱讀理解能力。 In this study, using fl ip concept mapping teaching strategy, hoping to enhance the students’ reading comprehension. The participants is fi fth-grade students in a mountainous area of New Taipei City. Select two classes as the experimental group and a control group, experimental group for teachers to use fl ip concept mapping teaching, control group for teachers to use traditional teaching. Quasi-experimental design, which lasted ten weeks a total of ten lessons. The conclusions as following below: 1. Through fl ip concept map teaching, the “extract information” and “inference messages” of reading comprehension in experimental group shows nosignificant difference, but better than control group in ability of “explain integration” and “comparative assessment”. 2. Through experiments, the higher learning effectiveness of experimental group students show no significant difference in “inference messages” with lower learning effectiveness students, but better than lower learning effectiveness students in ability of “extract information,” “explain integration” and “comparative assessment”