MétaCan
Menu
Back to cohort
Record W2153554254

Program Evaluation and Impact Assessment in International Non-Governmental Organizations (INGOs): Exploring Roles, Benefits, and Challenges

2013· article· en· W2153554254 on OpenAlexvenueaboutno aff
Stan Yu, Darrell McLaughlin

Bibliographic record

VenueCanadian journal of nonprofit and social economy research · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesManagementPublic relationsSociologyPhilosophyEconomics
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACTIn twenty-first century, call for International Non-governmental Organizations (INGOs) to demonstrate their effectiveness has become popularized. This has given rise to scholarly attention examining roles of program evaluation and impact assessment in assisting INGOs in demonstrating their effectiveness. While previous studies suggest that INGOs actively conduct program evaluation and impact assessment, this article explores perspectives of two Canadian INGOs on how they understand, use, and experience evaluation and assessment as it relates to their work. Our study uncovers three continuing challenges: evaluation and assessment are largely descriptive and lack more sophisticated analyses; efforts to conduct evaluation and assessment are consolidated within organizations' head offices, while staff members and volunteers are largely excluded; and evaluation and assessment remain rooted in paradigm of quantifiable results, which do not truly reflect nature of work being conducted on ground.RESUMEAu vingt-et-unieme siecle, on veut de plus en plus que les organisations non gouvernementales internationales (ONGI) demontrent leur efficacite. Ce desir a motive les chercheurs a se pencher sur les evaluations de programme et les etudes d'impact pour voir dans quelle mesure celles-ci peuvent aider les ONGI a montrer qu'elles sont efficaces. Des etudes anterieures suggerent que les ONGI menent de maniere concertee des evaluations de programme et des etudes d'impact. Cet article explore comment aujourd'hui deux ONGI canadiens comprennent, utilisent et vivent l'evaluation et la mesure de leur travail. Notre etude releve trois defis actuels : l'evaluation et la mesure tendent a etre descriptives sans offrir d'analyses plus poussees; ce sont les sieges sociaux des organismes qui gerent l'evaluation et la mesure en excluant ainsi bon nombre de fonctionnaires et volontaires; l'evaluation et la mesure se limitent au paradigme des resultats mesurables et par consequent elles ne refletent pas necessairement le veritable travail mene sur le terrain.Keywords I Mots cles : Non-governmental Organizations; Program evaluation; Impact assessment; Effectiveness; Qualitative research; International development / Organisation non gouvernementale internationale; Evaluation de programme; Etude d'impact; Efficacite; Recherche empirique; Developpement internationalINTRODUCTIONSince late 20th Century, call for International Non-governmental Organizations (INGOs) to demonstrate their effectiveness has become increasingly popularized (Abdel-Kader & Wadongo, 2011; Ebrahim & Rangan, 2010; Lecy, Schmitz, & Swedlund, 2011; Morley, Vinson, & Hatry, 2001; Moxham, 2009; Spar & Dail, 2002). This position is epitomized by Fisher (1997) who explains that in 21st Century, untainted image of INGOs as doing good to provide world with the service of a social need neglected by politics of State and greed of market, was suddenly met with sobering reality that after thirty years of increased numbers, budgets, and responsibilities, INGOs had yet to show world any substantial change (Atack, 1999). Edwards and Hulme (1996) further argue that ascription of INGOs as magic bullet for solving global issues often carries very little evidence to support it. For INGOs, this need to demonstrate effectiveness is intimately linked to parallel discussions of accountability and legitimacy, both of which have also been challenged by politicians, academics, media, and public alike (Atack, 1999; Gibelman & Gelman, 2004; Harsh, Mbatia, & Shrum, 2010; Nicolau & Simaens, 2009).The prominence of these debates has given rise to a stream of scholarly attention examining roles of program evaluation and impact assessment within INGO work (Alaimo, 2008; Bouchard, 2009; Campbell, 2002; Ebrahim & Rangan, 2010; Moxham, 2009). …

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.430
GPT teacher head0.517
Teacher spread0.087 · 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

Citations8
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCanadian journal of nonprofit and social economy researchSame topicEvaluation and Performance AssessmentFrench-language works237,207