Sample Audio: Apollo 11 One Small Step

2017 ◽  
Author(s):  
Keyword(s):  
Small Step

scholarly journals Beyond Last Words: Patterns of Linguistic and Interactional Behavior in a Historical Sample of Dying Hospital Patients

2021 ◽  
pp. 003022282110009
Author(s):  
Michael Erard
Keyword(s):  
Clinical Study ◽  
Social Context ◽  
Small Step ◽  
Left Behind ◽  
The Social ◽  
Canadian Physician ◽  
Hospital Patients ◽  
Historical Sample ◽  
William Osler ◽  
Frequent Observation

Patterns of linguistic and interactional behavior by people at the very end of their lives are not well described, partly because data is difficult to obtain. This paper analyzes descriptions of 486 deaths gathered from 1900 to 1904 in the first-ever clinical study of dying by noted Canadian physician, Sir William Osler. Only 16 patients were noted speaking, and only four canonical last words were reported. The most frequent observation by medical staff was that the deaths were quiet ( n = 30), though range of other behaviors were noted (e.g., moaning, delirium, seeming intention to speak). Osler's problematic study left behind data whose analysis is a small step toward empirically characterizing the linguistic and interactional details of a previously under-described phenomena as well as the importance of the social context in which they occur.

A small step towards the citizen sensor: A multi-purpose framework for mobile apps

2015 ◽  
Author(s):  
Daniel Aurelio Galeazzo ◽  
Daniele De Vecchi ◽  
Fabio Dell'Acqua ◽  
Pietro Demattei
Keyword(s):  
Mobile Apps ◽  
Small Step

One Small Step (film)

1978 ◽  
Vol 46 (11) ◽  
pp. 1203-1207
Author(s):  
WGBH‐TV Producer ◽  
Dietrich Schoeer
Keyword(s):  
Small Step

One small step for MIP towards automated metaphor identification?

2013 ◽  
Vol 3 (1) ◽  
pp. 77-99 ◽  
Author(s):  
Aletta G. Dorst ◽  
W.Gudrun Reijnierse ◽  
Gemma Venhuizen
Keyword(s):  
Large Scale ◽  
Chemical Processes ◽  
Small Step ◽  
Lexical Unit ◽  
Basic Meaning ◽  
General Rules ◽  
Natural Discourse ◽  
Authentic Data ◽  
Large Corpus

The manual annotation of large corpora is time-consuming and brings about issues of consistency. This paper aims to demonstrate how general rules for determining basic meanings can be formulated in large-scale projects involving multiple analysts applying MIP(VU) to authentic data. Three sets of problematic lexical units — chemical processes, colours, and sharp objects — are discussed in relation to the question of how the basic meaning of a lexical unit can be determined when human and non-human senses compete as candidates for the basic meaning; these analyses can therefore be considered a detailed case study of problems encountered during step 3.b. of MIP(VU). The analyses show how these problematic cases were tackled in a large corpus clean-up project in order to streamline the annotations and ensure a greater consistency of the corpus. In addition, this paper will point out how the formulation of general identification rules and guidelines could provide a first step towards the automatic detection of linguistic metaphors in natural discourse.

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