This book is like a favourite CD or LP [that's vinyl ;-) ], every track - chapter - is an ace - no duds. I wanted to start this review with the final chapter, but I'll pick that up in due course (iv?).
The book is structured in three parts:
- People
- Problems
- Places
I don't read horror specifically, so it is not often a book scares me from the get-go; but this one did.
Chapter 1 gets specific on the statistics of LNOB and sustainable development. The numbers make for grim reading and had me wondering how much sense I could make of the book overall from the albeit COVID tainted comfort of Wigan Pier. What stood out was the way the intro chapter set out the stall. Obviously, that's the purpose and while depressed at what was follow from the initial graphs, the structure and cogency provided its own impetus to read. The text is clear and very readable, the data, graphs, notes all have bite. While the SDGs are Sisyphean in nature, the intro is like a snowball that starts from the upper peaks and grows chapter by chapter in meaning and significance.
Obviously, Agenda 2030 looms large, but if you think in first reading of poverty, or to be more specific ultra-poor, income, education, Africa, development and finance you know the agenda to follow then for this community mental health nurse there are insights aplenty.
Chapter 2 combines two central issues in gender equality (by 2030) with 'Women on the Move'. The book draws significance to decade long issues that now constitute a specific SDG - #5 in this case. The book is up-to-date - oozing contemporaneity with #MeToo and background on the cussedness of the root causes of gender inequality. There's common sense too in the need for 'adaptable solutions that are fit for the complexity of the problem'. On first reading about the progress of feminist movements, but more recently experiencing resistance in access to and being able to inhabit civil spaces, this is more 'scary' than a horror story. Reflecting on the 'other' challenges and climate change especially and the role that feminism can play, this retrograde motion could be the stuff of nightmares. The chapter and book, as I will explain, drew my attention to the fact that while I tweet and post here on feminist issues: I am no feminist. The notes provide references and pointers to specific books on feminism. From this book I can see I should read one.
Organizations, such as, BRAC, Camfed, CARE Int. and Oxfam with authors clearly experts from academia and such key players in the field. The balances are not just financial, but a community program on women and girls can potentially prompt a backlash if men and boys and not engaged. I can see further relevance of being able to traverse individual-group, as Matthews and Nunn debate the merits and limitations of individual-based and need for social-based interventions. Yes, I can see how individual-based interventions can be apolitical (and how an axis can invoke several thresholds). To a text on feminism, I must add formal reading on intersectionality too, as the analysis called upon here (box 2.2) to make sense of social and income-based factors.
Several chapters raise the problem of scale, the lack of data, especially what is and can be measured. Without due care, false proxies can be used for measures and more simple interventions may be pursued because they are more easily quantified. This may be insufficient to fully understand the complexity of gender equality. The book is 'dynamic' throughout; with project and service-based action for the individual progressing then to movement-based at the social change level (CARE, 2017, p.31. Gender Equality Framework -- through Individual, Group, Communities to deliver Social Change).
Although in this first review-post I refer to feminism, the treatment in the book is balanced and also essential. I usually equate 'hope' with the intra- interpersonal domain. Of the many sources in this to follow-up, is evidence on the "science of hope" with Coates and MacMillan in chapter 3.
individual
|
INTERPERSONAL : SCIENCES
humanistic ----------------------------------------------- mechanistic
SOCIOLOGY : POLITICAL
|
group - population
Homi Kharas, John W. McArthur and Izumi Ohno, (Eds.) 2020. Leave No One Behind: Time for Specifics on the Sustainable Development Goals, Washington D.C.: Brookings Institution Press.
Despite efforts worldwide practicing nurses do not all see themselves as data modellers enthralled by IcT. IT isn't usually why they came to nursing, although many mature students may have started their career in the IT sector. Chapter 1 of Programming the Semantic Web highlights how a basic table is a model (p.6-7). So of course gifted with natural language we are all data modellers. Hodges model then is the ubiquitous high-level data model - a two-by-two table and a whole lot more.
orcid.org/0000-0002-0192-8965
