Book Review: Myles Mcgregor-Lowndes and Bob Wyatt (Eds.), Regulating Charities: The Inside Story, New York: Routledge (2017)
Bibliographic record
Abstract
REGULATING CHARITIES: THE INSIDE STORY is a fascinating amalgam that is part history, part chronology, and part storytelling about recent changes in how five historically connected common law countries approach regulating their charitable sectors. These countries are England and Wales, the United States, Canada, New Zealand and Australia, with each country’s evolutions being covered distinctively in at least two chapters. Chapter authors include those who have served as principle executives of their country’s primary regulatory body, members and chairs of government oversight commissions, a legislator, and leaders and practitioners from within the respective charitable sectors, including one with a decidedly state-level orientation. Many authors cross several categories, and some cut across multiple jurisdictions having served as advisors to others or substantive participants in international gatherings of charitable sector regulators. The book decidedly eschews a coordinated effort or commanded approach and successfully avoids merely comparing and contrasting among jurisdictions. Instead, the editors allow the chapter authors to communicate their perspectives on and experiences with the recent changes in the manner they believe will be most useful. In the process, the reader can draw their own comparisons, especially across the several key themes that organically emerge: the influence of political power, challenges balancing regulator independence vis a vis government and the sector, views of permissible proactive engagement by charitable sector entities in policy activity, and the effects in some countries of increasingly blurring lines with other sectors -- government and business. With this combination and approach, REGULATING CHARITIES satisfies certain curiosities, stokes others, and ignites new ones, perhaps especially in allowing the reader to decipher for him or herself just how much of the approaches taken by any given jurisdiction may or may not be readily transferrable to others. The book succeeds in demonstrating that appropriately regulating the charitable sector is challenging and that adapting from another jurisdiction(s) is not as easy nor as obvious as it might appear on the surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.043 | 0.035 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".