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Record W4408725873 · doi:10.1504/ijmed.2025.145146

Does social innovation promote the crowdfunding of technological projects

2025· article· en· W4408725873 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Management and Enterprise Development · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBusinessSocial innovationKnowledge managementMarketingPublic relationsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Promoters increasingly turn to crowdfunding platforms to finance and realise their projects. These platforms are an interesting alternative to traditional bank financing. Studies show that certain characteristics of the projects submitted, and their promoters influence the success of a crowdfunding campaign (target amount obtained or exceeded), particularly when the project is associated with social innovation. Based on data from 103 technological projects financed on the Kickstarter platform, our study shows that the number of contributors positively influences funding. However, our results reveal that technological projects associated with social innovation are less funded than those unrelated to it, suggesting that projects aimed at addressing social issues and generating positive community impact are perceived as less interesting by potential contributors. The results of this study provide further insights into the financing discourse of technological projects qualified as social innovation through crowdfunding.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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