The Pitchforks' Journey Through Multiple Time Frames

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.

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Patterns of Abuse in Male Same-Sex Relationships

Violence and Victims ◽

10.1891/0886-6708.23.5.617 ◽

2008 ◽

Vol 23 (5) ◽

pp. 617-636 ◽

Cited By ~ 38

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.

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Exploiting Multiple Time Frames

Time Compression Trading ◽

10.1002/9781119199854.part3 ◽

2015 ◽

pp. 89-90

Keyword(s):

Multiple Time ◽

Time Frames

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Use Multiple Time Frames

Trading Rules that Work ◽

10.1002/9781119202080.ch12 ◽

2015 ◽

pp. 71-75

Keyword(s):

Multiple Time ◽

Time Frames

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Forecasting Success on Large Projects: Developing Reliable Scales to Predict Multiple Perspectives by Multiple Stakeholders over Multiple Time Frames

Project Management Journal ◽

10.1002/pmj.21289 ◽

2012 ◽

Vol 43 (5) ◽

pp. 87-99 ◽

Cited By ~ 136

Author(s):

Rodney Turner ◽

Roxanne Zolin

Keyword(s):

Multiple Time ◽

Multiple Perspectives ◽

Multiple Stakeholders ◽

Time Frames

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Managing E-Mail Systems

Advances in Information Resources Management - Best Practices and Conceptual Innovations in Information Resources Management ◽

10.4018/978-1-60566-128-5.ch007 ◽

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.

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

ACM Transactions on Management Information Systems ◽

10.1145/3466689 ◽

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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