Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in ColombiaCitation formats

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Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia. / Jones, Pete; Carter, Jackie ; Renken, Jaco; Arbeláez Tobón, Magdalena .

89. ed. Manchester : University of Manchester, Global Development Institute, 2021. (Digital Development Working Paper Series).

Research output: Working paper

Harvard

APA

Vancouver

Jones P, Carter J, Renken J, Arbeláez Tobón M. Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia. 89 ed. Manchester: University of Manchester, Global Development Institute. 2021. (Digital Development Working Paper Series).

Author

Jones, Pete ; Carter, Jackie ; Renken, Jaco ; Arbeláez Tobón, Magdalena . / Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia. 89. ed. Manchester : University of Manchester, Global Development Institute, 2021. (Digital Development Working Paper Series).

Bibtex

@techreport{95d77266c6544311881f320150ad86e8,
title = "Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia",
abstract = "The UN Sustainable Development Goals (SDGs) create a global need to deliver on an agenda which relies heavily on quantitative data. This creates a demand for human capital with the requisite statistical and data skills to work on the challenges represented by the SDGs. Increasingly, long-term domestic solutions to the building of statistical capacities are being sought, in order to decrease the dependency on external support and ensure a sustainable flow of qualified professionals.In this paper we argue for the value of thinking of statistical capacity as a pipeline which needs to begin in the education system, and illustrate how investment in this end of the pipeline can deliver a more sustainable and long-term pathway to building up the holistic skills-base to enable the challenges of the SDGs to be tackled. We describe an existing tried-and-tested experiential learning model called Q-Step based on developing skills in the workplace, and propose that the successes of this partnership-driven model illustrate how {\textquoteleft}data fellowships{\textquoteright} can fulfil some of the unmet capacity needs of the data revolution for sustainable development.We illustrate our argument through a practical exploration of the development of such a learning model in Colombia. Although there are challenges in ensuring that educational access is equal, we demonstrate that there are significant opportunities and a data fellowships model opens doors for addressing local skills gaps to help deliver the SDGs.",
author = "Pete Jones and Jackie Carter and Jaco Renken and {Arbel{\'a}ez Tob{\'o}n}, Magdalena",
year = "2021",
language = "English",
series = "Digital Development Working Paper Series",
publisher = "University of Manchester, Global Development Institute",
address = "United Kingdom",
edition = "89",
type = "WorkingPaper",
institution = "University of Manchester, Global Development Institute",

}

RIS

TY - UNPB

T1 - Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia

AU - Jones, Pete

AU - Carter, Jackie

AU - Renken, Jaco

AU - Arbeláez Tobón, Magdalena

PY - 2021

Y1 - 2021

N2 - The UN Sustainable Development Goals (SDGs) create a global need to deliver on an agenda which relies heavily on quantitative data. This creates a demand for human capital with the requisite statistical and data skills to work on the challenges represented by the SDGs. Increasingly, long-term domestic solutions to the building of statistical capacities are being sought, in order to decrease the dependency on external support and ensure a sustainable flow of qualified professionals.In this paper we argue for the value of thinking of statistical capacity as a pipeline which needs to begin in the education system, and illustrate how investment in this end of the pipeline can deliver a more sustainable and long-term pathway to building up the holistic skills-base to enable the challenges of the SDGs to be tackled. We describe an existing tried-and-tested experiential learning model called Q-Step based on developing skills in the workplace, and propose that the successes of this partnership-driven model illustrate how ‘data fellowships’ can fulfil some of the unmet capacity needs of the data revolution for sustainable development.We illustrate our argument through a practical exploration of the development of such a learning model in Colombia. Although there are challenges in ensuring that educational access is equal, we demonstrate that there are significant opportunities and a data fellowships model opens doors for addressing local skills gaps to help deliver the SDGs.

AB - The UN Sustainable Development Goals (SDGs) create a global need to deliver on an agenda which relies heavily on quantitative data. This creates a demand for human capital with the requisite statistical and data skills to work on the challenges represented by the SDGs. Increasingly, long-term domestic solutions to the building of statistical capacities are being sought, in order to decrease the dependency on external support and ensure a sustainable flow of qualified professionals.In this paper we argue for the value of thinking of statistical capacity as a pipeline which needs to begin in the education system, and illustrate how investment in this end of the pipeline can deliver a more sustainable and long-term pathway to building up the holistic skills-base to enable the challenges of the SDGs to be tackled. We describe an existing tried-and-tested experiential learning model called Q-Step based on developing skills in the workplace, and propose that the successes of this partnership-driven model illustrate how ‘data fellowships’ can fulfil some of the unmet capacity needs of the data revolution for sustainable development.We illustrate our argument through a practical exploration of the development of such a learning model in Colombia. Although there are challenges in ensuring that educational access is equal, we demonstrate that there are significant opportunities and a data fellowships model opens doors for addressing local skills gaps to help deliver the SDGs.

M3 - Working paper

T3 - Digital Development Working Paper Series

BT - Strengthening the Skills Pipeline for Statistical Capacity Development to Meet the Demands of Sustainable Development: Implementing a Data Fellowship Model in Colombia

PB - University of Manchester, Global Development Institute

CY - Manchester

ER -