A typology of disintermediated giving and asking in the non‐profit sector
Bibliographic record
Abstract
Abstract Disintermediation is the ability to sell products and services directly to consumers without these having to pass or go through a ‘middleman’, such as travel agent or record company. With no product or service to sell to consumers, disintermediation in the non‐profit sector has been conceived as the giving of money directly to beneficiaries/end users, without the need to go through a ‘middleman’ charity—in other words, it is disintermediated giving. However, there is no consensus definition of what ‘disintermediated giving’ is or to what it applies. Much of the academic literature has focused on one form of disintermediated giving: crowdfunding, which is generally conducted on digital platforms. However, not all crowdfundraising/crowdfunding disintermediates charities from the process of giving; and not all disintermediation of charities from the giving process is accomplished via digital crowdfunding platforms. Further, there are examples of various forms of disintermediated giving, particularly, but not solely via crowdfunding platforms, that have raised questions about its practices, ethics, regulation and accountability. Finding robust and sustainable solutions to these issues first requires a coherent conceptualisation of disintermediation/disintermediated giving in the non‐profit sector. This paper attempts to do that by providing a typology of disintermediation/disintermediated giving. We examine the phenomenon of disintermediation in organisations that adopt the ‘traditional charity model’ (those which ask for and then convert donations into goods and services for beneficiaries) and look to see which functions and processes are subjected to disintermediation. This can be either the whole or part of that asking/converting process, which is replaced or bypassed by a different entity (individuals, commercial fundraising entities, or companies or charities that adopt an alternative approach to the ‘traditional charity model’). Our typology contains three main types of disintermediation: (A) the charity is disintermediated, with donations and support given directly by donors to beneficiaries; (B) the charity's fundraising function is disintermediated; (C) the charity's service provision to beneficiaries is disintermediated. Each of these raises ethical and regulatory issues, which we briefly explore.
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 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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.013 | 0.036 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".