MétaCan
Menu
Back to cohort
Record W2005023909 · doi:10.5430/ijhe.v1n2p55

The Challenge of Fundraising in Universities in Europe

2012· article· en· W2005023909 on OpenAlexvenueno aff
Carmen Pérez Esparrells, Eva M. de la Torre

Bibliographic record

VenueInternational Journal of Higher Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceBusiness

Abstract

fetched live from OpenAlex

The current financial context constitutes a challenge to European Higher Education Institutions in the sense that they must look to increasing their budgets with new activities. This context has led governments and European universities to promote not only the traditional private funding sources (such as transfer of knowledge or tuition fees), but also new means of raising supplementary philanthropic (private) funds for educational and research purposes. Therefore, the actual European context may also represents an opportunity for the development of their fundraising strategy, since a determined fundraising program will bring supplementary private funds to the institutions reducing the frequent internal resistance and increasing the willingness to overcome the lack of experience in this field in Europe. This paper highlights the change and opportunity that raising independent income from donations implies, in order to achieve excellence and add value to core funding. Here we review UK and Spain cases with special attention in two case studies: Cambridge University, as an example of a well-known prestigious European university with extensive experience in fundraising; and the University of Navarra, as a case of a relevant experience in fundraising policy in a private southern European university.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.147

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.032
GPT teacher head0.369
Teacher spread0.337 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Higher EducationSame topicNonprofit Sector and VolunteeringFrench-language works237,207