French Education in Science and the Puzzle of Retardation, 1790-1840

Este ensayo describe los altibajos de la educación científica francesa desde la década de 1780 hasta 1840. Comenzó con el descubrimiento de que en el Departamento del Norte las matemáticas y las ciencias abandonaron el plan de estudios de las universidades después de 1815. La educación pertenece a la historia cultural y en el caso francés tenemos otro ejemplo de un factor cultural que influye en el desarrollo industrial y contribuye al retraso. La clave para comprender esta extraña reacción al aprendizaje científico radica en la reacción católica a la Revolución Francesa.The essay traces the ups and downs of French scientific education from the 1780s to 1840. It began with the discovery that in the Department of the North mathematics and science dropped out of the curriculum of the colleges after 1815. Education belongs to cultural history and in the French case we have another example of a cultural factor playing into industrial development, and contributing to retardation. The key for understanding this rather bizarre reaction to scientific learning lies in the Catholic reaction to the French Revolution.Esse ensaio traça os altos e baixos da educação científica francesa de 1780 até 1840. Começa com a descoberta de que no departamento do norte, matemática e ciência foram descartadas do currículo universitário após 1815. A educação passou a ser papel da História cultural. No caso francês, temos outro exemplo de um fator cultural exercendo papel no desenvolvimento industrial e sua contribuição pra sua desaceleração. A chave para a compreensão desta um tanto bizarra reação ao saber científico está no fato da contrapartida católica frente à revolução francesa.peerReviewe

Student awareness of the Daily News-Record

The Daily News-Record is a local daily newspaper located in Harrisonburg, Virginia, a city with a population of about 52,000. The Daily News-Record\u27s print circulation is 26,000, while its digital circulation is 800. The paper also houses other local publications, such as the Rocktown Weekly, a free weekly publication that covers local news and the local music scene. James Madison University is a mid-sized public university also located in Harrisonburg, Virginia. The researcher wanted to understand JMU student awareness of local news sources, student consumption of news sources, student intention to read the local paper and whether there was a relationship with student community involvement, and student perception of campus opinion leaders. The survey research resulted in these major findings: 1) JMU students were mostly unaware of local news sources, but among local news sources, were most aware of the Daily News-Record; 2) students rely on online sources the most (Internet, Facebook, etc.) for gathering news; 3) students trust professors most as campus opinion leaders; 4) very few students had newspaper subscriptions, but when they did, their purpose of having one was to receive local news; 5) students were, by a very small margin, more likely to read and subscribe to the Rocktown Weekly compared to the Daily News-Record; 6) students more involved in the community were more aware of and more likely to read the Daily News-Record and Rocktown Weekly; 7) students more involved in the community had a higher intention to read and subscribe to the Daily News-Record and Rocktown Weekly; and 8) students who rely on print newspapers and print newspaper websites had a higher intention to read and subscribe to the Daily News-Record and Rocktown Weekly. Based on these primary research findings, goals, objectives, strategies, and tactics were created for a potential future campaign for Daily News-Record staff members to implement. A key public that would be targeted in this campaign was identified as a result of the research findings. This public has been named the Community Oriented Traditional Media Consumers (COTMC). This student public consumes more traditional forms of media, such as newspapers and newspaper websites, and is heavily involved in their community. Members of this public are more likely to read and subscribe to both publications, and students overall were more likely to subscribe to the Rocktown Weekly, so the COTMC public would be targeted in a campaign to increase their readership of the Rocktown Weekly. JMU students as a whole would also be targeted in this campaign, but because their intentions to read and subscribe to the publications were low, they would be targeted in a campaign to increase their overall awareness of both publications

Generating Natural Questions About an Image

There has been an explosion of work in the vision & language community during the past few years from image captioning to video transcription, and answering questions about images. These tasks have focused on literal descriptions of the image. To move beyond the literal, we choose to explore how questions about an image are often directed at commonsense inference and the abstract events evoked by objects in the image. In this paper, we introduce the novel task of Visual Question Generation (VQG), where the system is tasked with asking a natural and engaging question when shown an image. We provide three datasets which cover a variety of images from object-centric to event-centric, with considerably more abstract training data than provided to state-of-the-art captioning systems thus far. We train and test several generative and retrieval models to tackle the task of VQG. Evaluation results show that while such models ask reasonable questions for a variety of images, there is still a wide gap with human performance which motivates further work on connecting images with commonsense knowledge and pragmatics. Our proposed task offers a new challenge to the community which we hope furthers interest in exploring deeper connections between vision & language.Comment: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistic

A Survey of Current Datasets for Vision and Language Research

Integrating vision and language has long been a dream in work on artificial intelligence (AI). In the past two years, we have witnessed an explosion of work that brings together vision and language from images to videos and beyond. The available corpora have played a crucial role in advancing this area of research. In this paper, we propose a set of quality metrics for evaluating and analyzing the vision & language datasets and categorize them accordingly. Our analyses show that the most recent datasets have been using more complex language and more abstract concepts, however, there are different strengths and weaknesses in each.Comment: To appear in EMNLP 2015, short proceedings. Dataset analysis and discussion expanded, including an initial examination into reporting bias for one of them. F.F. and N.M. contributed equally to this wor

Language Models for Image Captioning: The Quirks and What Works

Two recent approaches have achieved state-of-the-art results in image captioning. The first uses a pipelined process where a set of candidate words is generated by a convolutional neural network (CNN) trained on images, and then a maximum entropy (ME) language model is used to arrange these words into a coherent sentence. The second uses the penultimate activation layer of the CNN as input to a recurrent neural network (RNN) that then generates the caption sequence. In this paper, we compare the merits of these different language modeling approaches for the first time by using the same state-of-the-art CNN as input. We examine issues in the different approaches, including linguistic irregularities, caption repetition, and data set overlap. By combining key aspects of the ME and RNN methods, we achieve a new record performance over previously published results on the benchmark COCO dataset. However, the gains we see in BLEU do not translate to human judgments.Comment: See http://research.microsoft.com/en-us/projects/image_captioning for project informatio

Linking relief and development

This Discussion Paper reports on a workshop on 'Linking Relief and Development', held at IDS, Sussex in March 1994. Development and relief often operate at cross-purposes, with different objectives, cultures and modes of operation. Change which leads to mutual reinforcement of the two is an attractive, even a necessary idea; though problematic in the growing number of cases where emergencies are related to conflict. A simple linear sequence, 'relief-rehabilitation-development' is not appropriate: more dynamic models are required, which recognize the complexity and diversity of livelihood strategies. And in selecting interventions, analysis is needed of cost, sequencing and institutional issues

An Overview of Industrial Relations in Kenya

The development of labour law in Kenya evolved in the voluntary tradition to what is today arguably one of the best institutionalized labour market governance systems in Africa. However, the persistence of labour unrest in various sectors of the Kenyan economy points to the need for a reexamination of the existing labour code in a bid to address areas of weakness for sound economic development. This paper traces the development of labour relations in Kenya from the pre independence period. Key milestones are discussed and examined in the light of best practices elsewhere in the world. It is the expectations of the authors that this paper will provide useful insight to labour officials both in government and business organizations in Kenya and elsewhere. Key words: labour laws, industrial labour relations, collective bargaining, tripartis