Perspectives on the Feldenkrais Method

2020 ◽  
Vol 9 (3) ◽  
pp. 214-227
Author(s):  
Roger Russell
Keyword(s):  
Multiple Time ◽  
Learning And Development ◽  
Feldenkrais Method ◽  
Biological Hierarchy ◽  
Multiple Levels ◽  
Time Frames

Developmental movement unfolds across multiple levels of a person’s biological hierarchy, and in multiple time frames. This article addresses some of the complexity of human moving, learning, and development that is captured in the lessons of the Feldenkrais Method®. It provides an overview of who Moshe Feldenkrais was and how he synthesized a body of work characterized by ontological, epistemological, and ethical stances that make his method unusual and provocative. An overview of his group and individual lessons, with examples, is followed by a closer look at how the complexity of the Feldenkrais method can be understood.

scholarly journals PLURALISM, THE PEOPLE, AND TIME IN LABOUR PARTY HISTORY, 1931–1964

2013 ◽  
Vol 56 (3) ◽  
pp. 729-756 ◽  
Author(s):  
JEREMY NUTTALL
Keyword(s):  
Labour Party ◽  
Social Progress ◽  
Multiple Time ◽  
The People ◽  
Negative Perceptions ◽  
Slow Moving ◽  
Progressive Potential ◽  
Time Frames ◽  
Pluralist Approach

ABSTRACTObserving the increasing, yet still partial exploration of pluralism, complexity and multiplicity in recent Labour party historiography, this article pursues a pluralist approach to Labour on two central, related themes of its middle-century evolution. First, it probes the plurality of Labour's different conceptions of time, specifically how it lived with the ambiguity of simultaneously viewing social progress as both immediate and rapidly achievable, yet also long term and strewn with constraints. This co-existence of multiple time-frames highlights the party's uncertainty and ideological multi-dimensionality, especially in its focus both on relatively rapid economic or structural transformation, and on much more slow-moving cultural, ethical, and educational change. It also complicates neat characterizations of particular phases in the party's history, challenging straightforwardly declinist views of the post-1945–51 period. Secondly, time connects to Labour's view of the people. Whilst historians have debated between positive and negative perceptions of the people, here the plural, split mind of Labour about the progressive potential of the citizenry is stressed, one closely intertwined with its multiple outlook on how long socialism would take. Contrasts are also suggested between the time-frames and expectations under which Labour and the Conservatives operated.

Patterns of Abuse in Male Same-Sex Relationships

2008 ◽  
Vol 23 (5) ◽  
pp. 617-636 ◽  
Author(s):  
Kim Bartholomew ◽  
Katherine V. Regan ◽  
Monica A. White ◽  
Doug Oram
Keyword(s):  
Partner Violence ◽  
Partner Abuse ◽  
Gay And Bisexual Men ◽  
Multiple Time ◽  
Bisexual Men ◽  
Same Sex ◽  
Unwanted Sexual Activity ◽  
And Bisexual ◽  
Almost All ◽  
Time Frames

Previous studies of abuse in male same-sex relationships have been limited by convenience samples and/or by incomplete assessments of partner abuse. We examined patterns of same-sex partner abuse in a random sample of 284 gay and bisexual men. Respondents reported on perpetration and receipt of physical, psychological, and sexual abuse over multiple time frames, as well as injuries resulting from abuse. Almost all respondents reported psychological abuse, more than one-third reported physical abuse, and 10% reported having engaged in unwanted sexual activity because of partner force or threats of force. More than half of recipients of partner violence reported sustaining injury. We found strong associations between different forms of abuse, and between severity of abuse receipt and perpetration.

How managing the interaction created a system of learning in a wholesale distribution model

2014 ◽  
Vol 28 (3) ◽  
pp. 17-20
Author(s):  
Simon R. Reese
Keyword(s):  
Knowledge Sharing ◽  
Learning System ◽  
Distribution Model ◽  
Traditional Learning ◽  
Learning And Development ◽  
Content Type ◽  
Wholesale Distribution ◽  
Multiple Levels ◽  
Traditional Learning Environments ◽  
Practical Implications

Purpose – The purpose of this paper is to illustrate how a manufacturer improved the interaction within the channel to facilitate a system of learning between three subsequent customer levels. Design/methodology/approach – The paper provides an example of how a manufacturer designed steps to change the traditional interactions between the customer levels and place themselves in the middle of a knowledge-sharing environment. Findings – To best ensure consistency in knowledge sharing across the multiple levels, the learning and development (L&D) practitioner should examine the interactions and identify the unique benefits to encourage all members to freely engage in the learning system. Practical implications – Managing the learning system allows the manufacturer to manage knowledge sharing and reinforce a consistent message. Originality/value – The paper offers the steps undertaken and the benefits resulting from the improved interactions. The example provides the L&D professionals areas into which they can expand traditional learning environments.

scholarly journals A semantic parsing pipeline for context-dependent question answering over temporally structured data

2021 ◽  
pp. 1-25
Author(s):  
Charles Chen ◽  
Razvan Bunescu ◽  
Cindy Marling
Keyword(s):  
Speech Recognition ◽  
Question Answering ◽  
Data Augmentation ◽  
Short Term Memory ◽  
Context Dependency ◽  
Sensor Data ◽  
Multiple Time ◽  
Semantic Parsing ◽  
Multiple Levels ◽  
And Behavior

Abstract We propose a new setting for question answering (QA) in which users can query the system using both natural language and direct interactions within a graphical user interface that displays multiple time series associated with an entity of interest. The user interacts with the interface in order to understand the entity’s state and behavior, entailing sequences of actions and questions whose answers may depend on previous factual or navigational interactions. We describe a pipeline implementation where spoken questions are first transcribed into text which is then semantically parsed into logical forms that can be used to automatically extract the answer from the underlying database. The speech recognition module is implemented by adapting a pre-trained long short-term memory (LSTM)-based architecture to the user’s speech, whereas for the semantic parsing component we introduce an LSTM-based encoder–decoder architecture that models context dependency through copying mechanisms and multiple levels of attention over inputs and previous outputs. When evaluated separately, with and without data augmentation, both models are shown to substantially outperform several strong baselines. Furthermore, the full pipeline evaluation shows only a small degradation in semantic parsing accuracy, demonstrating that the semantic parser is robust to mistakes in the speech recognition output. The new QA paradigm proposed in this paper has the potential to improve the presentation and navigation of the large amounts of sensor data and life events that are generated in many areas of medicine.

Managing E-Mail Systems

2011 ◽  
pp. 103-115
Author(s):  
Aidan Duane ◽  
Patrick Finnegan
Keyword(s):  
Electronic Monitoring ◽  
Single Case ◽  
Multiple Time ◽  
Monitoring And Control ◽  
Transformative Action ◽  
Negative Impacts ◽  
Time Frames ◽  
And Control ◽  
A Company

An email system is a critical business tool and an essential part of organisational communication. Many organisations have experienced negative impacts from email and have responded by electronically monitoring and restricting email system use. However, electronic monitoring of email can be contentious. Staff can react to these controls by dissent, protest and potentially transformative action. This chapter presents the results of a single case study investigation of staff reactions to electronic monitoring and control of an email system in a company based in Ireland. The findings highlight the variations in staff reactions through multiple time frames of electronic monitoring and control, and the chapter identifies the key concerns of staff which need to be addressed by management and consultants advocating the implementation of email system monitoring and control.

Machine Learning and Survey-based Predictors of InfoSec Non-Compliance

2022 ◽  
Vol 13 (2) ◽  
pp. 1-20
Author(s):  
Byron Marshall ◽  
Michael Curry ◽  
Robert E. Crossler ◽  
John Correia
Keyword(s):  
Feature Selection ◽  
Security Policy ◽  
Prediction Models ◽  
Training Programs ◽  
Selection Process ◽  
Multiple Time ◽  
Compliance Behavior ◽  
Systematic Feature ◽  
Tree Models ◽  
Time Frames

Survey items developed in behavioral Information Security (InfoSec) research should be practically useful in identifying individuals who are likely to create risk by failing to comply with InfoSec guidance. The literature shows that attitudes, beliefs, and perceptions drive compliance behavior and has influenced the creation of a multitude of training programs focused on improving ones’ InfoSec behaviors. While automated controls and directly observable technical indicators are generally preferred by InfoSec practitioners, difficult-to-monitor user actions can still compromise the effectiveness of automatic controls. For example, despite prohibition, doubtful or skeptical employees often increase organizational risk by using the same password to authenticate corporate and external services. Analysis of network traffic or device configurations is unlikely to provide evidence of these vulnerabilities but responses to well-designed surveys might. Guided by the relatively new IPAM model, this study administered 96 survey items from the Behavioral InfoSec literature, across three separate points in time, to 217 respondents. Using systematic feature selection techniques, manageable subsets of 29, 20, and 15 items were identified and tested as predictors of non-compliance with security policy. The feature selection process validates IPAM's innovation in using nuanced self-efficacy and planning items across multiple time frames. Prediction models were trained using several ML algorithms. Practically useful levels of prediction accuracy were achieved with, for example, ensemble tree models identifying 69% of the riskiest individuals within the top 25% of the sample. The findings indicate the usefulness of psychometric items from the behavioral InfoSec in guiding training programs and other cybersecurity control activities and demonstrate that they are promising as additional inputs to AI models that monitor networks for security events.

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