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Record W7028581573

Exploring the role of international non-governmental organizations in rebuilding conflict-affected societies through educational project work

2008· other· en· W7028581573 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2008
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)PeacebuildingTransformational leadershipIntervention (counseling)Civil societyQualitative researchProject managementProject sponsorship
DOInot available

Abstract

fetched live from OpenAlex

Non-governmental organizations (NGOs) have become increasingly utilized in the rebuilding of war-torn countries. This thesis is a grounded-theory qualitative study of the role of NGO educational projects in re-building civil society in Afghanistan as well as other conflict-affected nations. Six NGO project directors and field officers working on project work in Afghanistan were selected as interview participants. Analysis of the interview narratives revealed several key findings. These key findings suggest that while NGO officials recognize several root causes of conflict in their work contexts, conflict’s causes have limited impact on their project design. However, NGO officials believed educational project work had transformational potential. Further, NGO officials believed their project work to be successful in its development and peacebuilding goals, but suggested a need for increased project time frames. Finally, they believed their NGO project work to be but one track in a multi-track intervention into conflict-affected countries.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.011
Scholarly communication0.0070.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.177
Teacher spread0.167 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2008
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)→French-language works237,207→