A research agenda for financial resources within the household by FranBennett, SilviaAvram, SlobhanAusten, Eds. 2024. 264 pp. <scp>ISBN</scp>: 978 1 80220 399 8 (cased). <scp>ISBN</scp>: 978 1 80220 400 1 (<scp>eBook</scp>)
Bibliographic record
Abstract
This book about researching financial resources in the household is edited by three leading academics (two Fellows from the UK and a Professor Emerita of Economics from Australia) and contains 15 contributed chapters by authors from Australia, Britain, Scotland, the Asia-Pacific region, Luxembourg, Lesotho, Japan, South Africa, Ghana, and Canada. Most of the authors are academics with sociology, social science, or economics backgrounds such as the London School of Economics. Others work for institutes, centers, and organizations, often as Directors or CEOs. The eclectic nature of this mix, especially of countries, brings richness and depth to an important topic—the way in which a household controls and allocates its resources impacting standards of living. It includes money or financial discussions of the interactions among family members and the greater society. The book is well referenced and written for academics and policymakers but is also suitable for graduate classes where a wider point of view leads to discussion of complexities from a global perspective. As the title suggests, this book looks toward the future; what research needs to be done? Qualitative and quantitative research are covered. Definitions of key terms such as household deprivation, income, poverty, and family unit on pages 101–102 would be useful in classes and in research. A household is defined as people living in the same private dwelling and sharing some expenditures—this definition is specified by the EU. Authors, London-based Tania Burchardt and Elena Karagiannaki of ‘Many Mouths Under One Roof: Multigenerational Families in Europe Sharing Resources Within Households’, provide a practical side to this topic. They cover poverty risks and uneven sharing in Chapter six. Is this resource discussion important? Yes, it is. This point was made over and over again in the forward written by Jan Pahl of the University of Kent. It is important to know how resources are allocated and shared. She asks how are resources distributed and managed? She suggests that this discussion of roles within relationships, well-being, and patterns of behavior requires a range of disciplinary routes. Who has more influence in decision-making? The editors say in their brief overview of research on resources in the household that decision-making is fundamental to understanding this topic. Theoretical frameworks, such as bargaining theory in the first chapter by Canadian Frances Woolley, are explored along with measurement and data. The book is divided into three parts. Part I is entitled Concepts, Tools, Measures, and Challenges. It has five chapters. Part II is entitled Recent Research into Resources within the Household: New Directions Taken, with five chapters. Part III is entitled The Interrelationship Between Resources within the Household and Policy, and also has five chapters, ending with the 15th chapter on the meaning of social security money within households. An obvious strength of the book is its gathering of information and expertise from many countries, some small and some large in size and influence. Another is the mix of social and economic expertise and the applications to policy. Given 15 chapters, not all the countries in the world could be covered nor a thorough overview given of the contributions of resource management, personal and family finance, family studies, and consumer economics by leading North, Central, and South American scholars with the noted exception of the Canadian author of the first chapter. That said, putting these together with this book would make for a stimulating graduate-level class, opening up a world view and the overarching recognition of the financial issues households face from inflation to pandemic response to effects of migration. Feminist scholarship and gender studies are covered too. Childhood deprivation and poverty is a theme. Ageism is not ignored. This book does not shrink from the harsher sides of economic abuse the subject of Chapter eight. Chapter nine delves into the morality of money. The different research subjects and methods outlined could lead to new studies and dissertations. This book stimulates a lot of thought about conditions in a variety of countries and the research gaps that exist. There is, indeed, a lot of work to be done in financial research and the editors and chapter contributors are to be congratulated for tackling a difficult and complex subject affecting us all.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".