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Record W2553254625 · doi:10.56645/jmde.v12i27.454

Debate on the Appropriate Methods for Conducting Impact Evaluation of Programs within the Development Context

2016· article· en· W2553254625 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

VenueJournal of MultiDisciplinary Evaluation · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsImpact evaluationContext (archaeology)Program evaluationComputer scienceManagement scienceIntervention (counseling)Impact assessmentProcess managementEvaluation methodsRisk analysis (engineering)PsychologyPolitical scienceBusinessEngineeringMedicine

Abstract

fetched live from OpenAlex

Background: Donors and decision-makers use impact evaluation reports to assess the effectiveness of development programs and identify ways to improve the design and implementation of projects, programs, and policies in developing countries. Purpose: This paper will explore the existing published impact evaluation literature on development programs and provide an overview of the types of approaches and methods that are being used to conduct impact evaluations. Setting: NA Intervention: NA Research Design: The paper will examine published program evaluation literature in order to shed light on issues related to appropriate methods for impact evaluations of development programs. Data Collection and Analysis: Literature review. Findings: The paper will conclude by suggesting a list of approaches and methods that can be used to conduct impact evaluations of programs within the development context.

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)0.199
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1990.016
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 science0.0010.000
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 head0.623
GPT teacher head0.614
Teacher spread0.009 · 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