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Record W2623362778

Participatory approach to community-based curriculum development for the Living With Elephants outreach program in Botswana / Suzanne Katherine Hamel. --

2017· dissertation· en· W2623362778 on OpenAlexfundno aff
Suzanne Katherine Hamel

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
FundersLakehead University
KeywordsOutreachCitizen journalismCurriculumSociologyLibrary scienceGender studiesGeographyVisual artsPedagogyPolitical scienceArtLawComputer science
DOInot available

Abstract

fetched live from OpenAlex

There are increasing conflicts arising between humans and elephants throughout Africa and Asia.The Republic o f Botswana, which has one of the world's largest elephant populations, is no exception.One strategy for improving relations between humans and elephants may be participatory and community-based environmental education initiatives.Thus the goal o f my project was to work with the non-governmental organization "Living With Elephants Foundation" (LWE) and local Batswanan communities to apply participatory research methods to the collaborative development of an elephant educational outreach program in Botswana.This study describes the process and the results of efforts to collaboratively develop, test and modify educational programming that aimed to contribute to a sustainable relationship between people and elephants.The study had three phases.Phase I involved reviewing academic and non governmental organization literature and determining needs of the elephants and people of Botswana through conducting key informant interviews and focus group discussions.Phase II began with an analysis of the initial emergent themes in the data collected in the previous phase in order to develop the goal and objectives and the first draft of the LWE Education Outreach Program.Phase II also involved an evaluation o f this version of the program, and was based on student, teacher and community feedback, and the collection o f drawings from Botswana students participating in the LWE outreach program.This phase created a space for further revisions, development of follow-up activities, and identification of further needs.Phase III occurred in Canada where I reviewed all the data collected, conducted further analysis as needed and wrote the thesis.This thesis was shared with LWE and a summary will be provided to all interested stakeholders.

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)0.007
metaresearch head score (Gemma)0.004
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 score0.025
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.087
GPT teacher head0.294
Teacher spread0.206 · 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
Published2017
Admission routes1
Has abstractyes

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