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Record W7066616066

The Impact of NGO Classes on Students Being Change Agents

2019· other· en· W7066616066 on OpenAlexaboutno aff

Bibliographic record

VenueCSUN ScholarWorks (California State University, Northridge) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Government (linguistics)Subject (documents)AttendanceAgency (philosophy)Service (business)
DOInot available

Abstract

fetched live from OpenAlex

This research examines two courses, ???NGOs and Social Service Outreach??? and ???International NGO Fieldwork in Vancouver,??? offered at California State Polytechnic University, Pomona, and their impact on higher education students being change agents. An in-depth summary and overview of ???NGOs and Social Service Outreach??? is provided as this course was the foundation for students??? technical training about NGO???s. Participant observation was used to provide a summary of lectures and excursions in Vancouver and Victoria for the course, ???International NGO Fieldwork in Vancouver.??? This project analyzes qualitative data from secondary research to identify the impact each class has on student involvement and to determine students??? motivation to get involved in NGO work. The project concisely integrates theoretical literature on change agents, leadership, motivation, and study abroad. Results indicate that students felt empowered, developed personal and professional skills, increased awareness, and wanted to make a difference after taking the ???NGOs and Social Service Outreach??? course at Cal Poly Pomona. Students who participated in the ???International NGO Fieldwork in Vancouver??? program expressed increased awareness, inspiration, empowerment and motivation after this study abroad experience. Students were motivated to get involved in NGO work because they want to help others, increase equality, make a difference in their communities, solve problems and because they feel like NGO work is rewarding. The results from this research can guide faculty members and students about how acquiring technical skills and exposure to NGOs during study abroad courses can impact students on being change agents. Future programs should integrate and intensify experiential learning by including a service-learning component in the fieldwork course.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0080.002
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.027
GPT teacher head0.294
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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