Charitable giving and the disintermediation of the non‐profit and voluntary sectors
Bibliographic record
Abstract
Journal of Philanthropy and MarketingEarly View e1806 EDITORIAL Charitable giving and the disintermediation of the non-profit and voluntary sectors Meredith Niles, Meredith Niles Plan International, London, UKSearch for more papers by this authorRita Kottasz, Corresponding Author Rita Kottasz [email protected] Kingston University, London, UK[email protected]Search for more papers by this authorWalter Wymer, Walter Wymer orcid.org/0000-0002-5864-2829 University of Lethbridge, Lethbridge, Alberta, CanadaSearch for more papers by this author Meredith Niles, Meredith Niles Plan International, London, UKSearch for more papers by this authorRita Kottasz, Corresponding Author Rita Kottasz [email protected] Kingston University, London, UK[email protected]Search for more papers by this authorWalter Wymer, Walter Wymer orcid.org/0000-0002-5864-2829 University of Lethbridge, Lethbridge, Alberta, CanadaSearch for more papers by this author First published: 11 July 2023 https://doi.org/10.1002/nvsm.1806Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. REFERENCES Cherry, M. A. (2016). Beyond misclassification: The digital transformation of work. Comparative Labor Law and Policy Journal, 37(3), 577– 602. Duffy, B., Hall, S., Pope, S., & O'Leary, D. (2013). Attitudes of different generations to the welfare system. Joseph Rowntree Foundation. file:///C:/Users/KU58778/Downloads/Attitudes-of-different-generations-to-the-welfare-system.pdf Economist. (2006). The birth of philanthrocapitalism. Economist. https://www.economist.com/special-report/2006/02/25/the-birth-of-philanthrocapitalism Ferrell-Schweppenstedde, D. (2023). Key challenges and opportunities facing the charity sector. Charities Aid Foundation. https://www.cafonline.org/about-us/blog-home/charities-blog/challenges-and-opportunties-facing-charity-sector Gawer, A. (2014). Bridging differing perspectives on technological platforms: Toward an integrative framework. Research Policy, 43(7), 1239– 1249. Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015). Working with machines: The impact of algorithmic and data-driven management on human workers. In Proceedings of the 33rd annual ACM conference on human factors in computing systems, Seoul, Republic of Korea, 18–23 April. McGoey, L. (2012). Philanthrocapitalism and its critics. Poetics, 40(2), 185– 199. Meoli, M., & Vismara, S. (2021). Information manipulation in equity crowdfunding markets. Journal of Corporate Finance, 67, 101866. Moellendorf, D. (2022). Mobilizing hope: Climate change and global poverty. Oxford University Press. Rowe, E. E. (2022). Philanthrocapitalism and the state: Mapping the rise of venture philanthropy in public education in Australia. ECNU Review of Education, 209653112211288. Trelstad, B. (2016). Impact investing: A brief history. Capitalism & Society, 11(2), 1– 14. Wait, S. (2022). ‘Cost-of-giving crisis’: Are charity donations dropping? Civil Society (Fundraising). https://www.civilsociety.co.uk/fundraising/cost-of-giving-crisis.html Wajcman, J. (2006). New connections: Social studies of science and technology and studies of work. Work, Employment and Society, 20(4), 773– 786. Early ViewOnline Version of Record before inclusion in an issuee1806 ReferencesRelatedInformation
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".