Understanding Teacher Leadership in Middle School Mathematics: A Collaborative Research Effort

We report findings from a collaborative research effort designed to examine how teachers act as leaders in their schools. We find that teachers educated by the Math in the Middle Institute act as key sources of advice for colleagues within their schools while drawing support from a network consisting of other teachers in the program and university-level advisors. In addition to reporting on our findings, we reflect on our research process, noting some of the practical challenges involved, as well as some of the benefits of collaboration

Models to represent linguistic linked data

As the interest of the Semantic Web and computational linguistics communities in linguistic linked data (LLD) keeps increasing and the number of contributions that dwell on LLD rapidly grows, scholars (and linguists in particular) interested in the development of LLD resources sometimes find it difficult to determine which mechanism is suitable for their needs and which challenges have already been addressed. This review seeks to present the state of the art on the models, ontologies and their extensions to represent language resources as LLD by focusing on the nature of the linguistic content they aim to encode. Four basic groups of models are distinguished in this work: models to represent the main elements of lexical resources (group 1), vocabularies developed as extensions to models in group 1 and ontologies that provide more granularity on specific levels of linguistic analysis (group 2), catalogues of linguistic data categories (group 3) and other models such as corpora models or service-oriented ones (group 4). Contributions encompassed in these four groups are described, highlighting their reuse by the community and the modelling challenges that are still to be faced

Introduction

By highlighting relations between experimental and theoretical work, this volume explores new ways of addressing the problem of concept composition, which is one of the central challenges in the study of language and cognition. An introductory chapter lays out the background to the problem. The subsequent chapters by leading scholars and younger researchers in psychology, linguistics and philosophy, aim to explain how meanings of different complex expressions are derived from simple lexical concepts, and to analyze how these meanings connect to concept representations. This work demonstrates an important advance in the interdisciplinary study of concept composition, where points of convergence between cognitive psychology, linguistics and philosophy emerge and lead to new findings and theoretical insights

The algebra of lexical semantics

Abstract. The current generative theory of the lexicon relies primar-ily on tools from formal language theory and mathematical logic. Here we describe how a different formal apparatus, taken from algebra and automata theory, resolves many of the known problems with the gener-ative lexicon. We develop a finite state theory of word meaning based on machines in the sense of Eilenberg [11], a formalism capable of de-scribing discrepancies between syntactic type (lexical category) and se-mantic type (number of arguments). This mechanism is compared both to the standard linguistic approaches and to the formalisms developed in AI/KR. 1 Problem Statement In developing a formal theory of lexicography our starting point will be the informal practice of lexicography, rather than the more immediately related for-mal theories of Artificial Intelligence (AI) and Knowledge Representation (KR). Lexicography is a relatively mature field, with centuries of work experience an

Greenhushing: the deliberate under communicating of sustainability practices by tourism businesses

Greenhushing selectively communicates fewer pro-sustainability actions by businesses than are practiced; based on a perception of customers’ rights to consumerism. We first studied the gap between the communication of sustainability practices in the audits and websites of 31 small rural tourism businesses in the Peak District National Park (UK). The analysis showed that businesses only communicate 30% of all the sustainability actions practiced. Their websites emphasised customer benefits, using explicit, affective, experiential and active language that legitimises the customers’ hedonistic use of the landscape, while downplaying complex issues and normalising sustainability to reduce customer guilt. Just one website mentioned climate change. We found that greenhushing results from a low moral intensity, masking potentially negative consequences of perceived lower competence, whilst protecting business from more cynical consumers who may interpret their statements as hypocritical. Subsequent textual analysis and interviews were used to understand how communication constitutes these organisations. We propose that greenhushing reshapes and constitutes tourism businesses through their communications. Moreover, greenhushing is a form of public moralisation that adopts communication practices similar to greenwashing, reflecting the social norms expected from a business; however, in this case, located in a moral muteness, rather than moral hypocrisy, that businesses accept but resent

Corpus annotation for mining biomedical events from literature

<p>Abstract</p> <p>Background</p> <p>Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation.</p> <p>Results</p> <p>We have completed a new type of semantic annotation, event annotation, which is an addition to the existing annotations in the GENIA corpus. The corpus has already been annotated with POS (Parts of Speech), syntactic trees, terms, etc. The new annotation was made on half of the GENIA corpus, consisting of 1,000 Medline abstracts. It contains 9,372 sentences in which 36,114 events are identified. The major challenges during event annotation were (1) to design a scheme of annotation which meets specific requirements of text annotation, (2) to achieve biology-oriented annotation which reflect biologists' interpretation of text, and (3) to ensure the homogeneity of annotation quality across annotators. To meet these challenges, we introduced new concepts such as Single-facet Annotation and Semantic Typing, which have collectively contributed to successful completion of a large scale annotation.</p> <p>Conclusion</p> <p>The resulting event-annotated corpus is the largest and one of the best in quality among similar annotation efforts. We expect it to become a valuable resource for NLP (Natural Language Processing)-based TM in the bio-medical domain.</p

Can minimalism about truth embrace polysemy?

Paul Horwich is aware of the fact that his theory as stated in his works is directly applicable only to a language in which a word, understood as a syntactic type, is connected with exactly one literal meaning. Yet he claims that the theory is expandable to include homonymy and indexicality and thus may be considered as applicable to natural language. My concern in this paper is with yet another kind of ambiguity - systematic polysemy - that assigns multiple meanings to one linguistic type. I want to combine the characteristics of systematic polysemy with the Kaplanian insight that meanings of expressions may be defined by semantic rules which assign content in context and to ask the question if minimalism about truth and meaning is compatible with such rule-based systematic polysemy. I will first explain why the expressions that exhibit rule-based systematic polysemy are difficult to combine with a truth theory that is based on a use theory of meaning before proceeding to argue that indexicals and proper names are such expressions