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Record W4386574708 · doi:10.1002/nvsm.1820

A typology of disintermediated giving and asking in the non‐profit sector

2023· article· en· W4386574708 on OpenAlexaff
Ian MacQuillin, Rita Kottász, Juniper Locilento, Neil Gallaiford

Bibliographic record

VenueJournal of Philanthropy and Marketing · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsSt. Thomas HospitalToronto Metropolitan UniversityToronto Arts Foundation
Fundersnot available
KeywordsDisintermediationTypologyReification (Marxism)BusinessNetnographyProfit (economics)Goods and servicesPublic relationsMarketingEconomicsSociologyPolitical scienceLawSocial mediaFinanceMarket economy

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.238
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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