The Reproducibility of Governance Indicators

Mapping Intimacies ◽

10.1093/oso/9780198817062.003.0009 ◽

2018 ◽

Author(s):

Christopher Gandrud

Keyword(s):

Best Practices ◽

Shared Governance ◽

Data Gathering ◽

Status Quo ◽

Full Data ◽

Governance Indicator ◽

Governance Indicators ◽

Indicator Development ◽

The Status ◽

Version Control System

Reproducibility is a core tenant of scientific enquiry, including the study of governance and government outputs. Having full access to the data and procedures that researchers used to study a phenomenon is vital for being able to understand and trust their findings. This chapter sets out best practices for the reproducibility of governance indicators. For a governance indicator project to be ‘really reproducible’, the full data as well as data gathering and analysis procedures should be easily and persistently accessible. Indicator development should be fully documented, especially via a version control system. The chapter surveys the status quo level of reproducibility among prominent governance indicator projects. While most had some reproduction material available, none were really reproducible. The chapter concludes with recommendations, including calling for a shared governance indicator hosting service that focuses on encouraging reproducibility.

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Generation I(mmersion) – How to Meet Learner Expectations of Tomorrow

International Journal of Advanced Corporate Learning (iJAC) ◽

10.3991/ijac.v9i1.5241 ◽

2016 ◽

Vol 9 (1) ◽

pp. 19 ◽

Cited By ~ 2

Author(s):

Kai Erenli

Keyword(s):

Best Practices ◽

Generation X ◽

Generation Y ◽

State Of The Art ◽

Status Quo ◽

Learning Spaces ◽

The Status ◽

E Learning ◽

Tools And Techniques ◽

And Control

Today’s teachers mainly belong to the so-called “Generation X” while learners are most often described as “Generation Y” or “Millennials”. Most current discussions of learning methods are being held in view of the status quo. But what about the learners of tomorrow? What expectations do the learners of tomorrow have? Which methods and tools will the teachers of tomorrow have in stock to meet these expectations? “The old learning spaces, dominated by the immensely successful organizations of the industrial era like schools and universities, are struggling to maintain authority and control over the definition and certification of knowledge while at the same time remaining true to the stated mandate of helping to equip people and society for a life where learning is much more heterogeneous and heterarchical”[11]. Therefore, wouldn´t it be good to have a toolset ready and be able to choose the appropriate tools and techniques right on time? Reflecting on publications, expert interviews and state-of-the-art best practices, this paper attempts to draw a picture of the future (e-)learning scenario. To give the next generation a name, “Generation I(mmersion)” has been chosen. Despite breaking the X, Y, Z sequence, this name highlights the state of “Immersion”, which educators and learners of tomorrow will/might find themselves in.

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CORP: Improving the status quo for measuring whole body sweat losses

Journal of Applied Physiology ◽

10.1152/japplphysiol.00433.2017 ◽

2017 ◽

Vol 123 (3) ◽

pp. 632-636 ◽

Cited By ~ 22

Author(s):

Samuel N. Cheuvront ◽

Robert W. Kenefick

Keyword(s):

Best Practices ◽

Heat Balance ◽

Measurement Errors ◽

Status Quo ◽

Whole Body ◽

Potential Measurement ◽

Acute Change ◽

The Status ◽

The Common ◽

Body Heat

The measurement of whole body sweat losses (WBSL) is important to the study of body heat balance, body water balance, establishing guidelines for water and electrolyte consumption, and the study of metabolism and health. In principal, WBSL is measured by an acute change in body mass (ΔBM) in response to a thermoregulatory sweating stimulus. In this Cores of Reproducibility in Physiology (CORP) review, we revisit several basic, but rarely discussed, assumptions important to WBSL research, including the common equivalences: mass = weight = water = sweat. Sources of large potential measurement errors are also discussed, as are best practices for avoiding them. The goal of this CORP review is to ultimately improve the accuracy, reproducibility, and application of WBSL research.

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