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Record W7030494167

Navigating ethical terrains: perspectives on "research ethics" in Kakuma refugee camp

2019· dissertation· en· W7030494167 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
FundersMcGill University
KeywordsRefugeeEthnographyScholarshipResearch ethicsQualitative researchAsylum seekerEthical issues
DOInot available

Abstract

fetched live from OpenAlex

A dearth of scholarship has examined the phenomenon of research ethics from the perspectives of young people living in refugee camps.The following three-manuscript dissertation explores how refugee young people, living in Kakuma refugee camp (Kenya), comprehend and make sense of participating in research.By examining theoretical constructions of research ethics with refugee young people, who have previously participated in research, this dissertation inquires how research participants report the impact and effects of participating as researched subjects.Via a critical ethnographic methodology, including qualitative interview methods, 31 refugee young people explored the underpinnings of "ethical research" in Kakuma refugee camp.The participants were positioned as the experts of research ethics in Kakuma refugee camp.Data indicate that multiple contradictions and discrepancies exist between the values of research ethics for (a) refugee young people in Kakuma refugee camp and (b) the foundations of ethical research scholarship/protocols.For instance, participants reported that researchers did not necessarily provide "benefits" or "respect" during their previous research experiences.Given the disparities in the constructions of research ethics, multiple theoretical prisms were utilized throughout the three manuscripts: postcolonialism approaches, anti-oppression research, self-reflexivity, power, and decolonizing practices.By situating refugee young people as experts in research ethics, this dissertation also presents participant-centered research recommendations for future researchers.These include providing feedback to participants, exercising direct and transparent communication, following up with research recommendations, and reflecting on one's research and personal objectives in Kakuma.Findings of this research reaffirm the responsibility of social work researchers, practitioners, and educators to explore "ethics" when engaging with communities that experience displacement, marginalization, and oppression.support, energy, love, and guidance that framed this wild and majestic process currently feels unfeasible.While I'm indubitably left with a plethora of existential and practical queries related to this project, one aspect feels clear: this experience was one of the most existentially profound and riveting that I've been privileged enough to embrace.How could I possibly not commence with the backbone of my doctoral studies: Myriam Denov?! Myriam's gracious and overwhelmingly supportive mentorship and guidance only amplified throughout my process.Thanks to Myriam's leadership, critique, personality, and encouragement, I have irrefutably advanced my academic writing, critique, nuance, point of reference, interest, and position as a social worker and social work researcher.Throughout my journey, Myriam's consistent desire for me to explore: "How will this work impact social work practice, theory, education, and research?"will incessantly guide me well after my training at McGill.Without Myriam, my academic trajectory would clearly look different.I also am particularly grateful to my two doctoral committee members-Sara Kahn and Steven High.Both scholars were monumental in sharing their expertise and encouragement in a critical, yet very thoughtful and supportive manner.Shari Brotman was also influential and supportive with my

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)0.088
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.463

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0880.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0440.112
Scholarly communication0.0270.023
Open science0.0030.018
Research integrity0.0110.018
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
GPT teacher head0.541
Teacher spread0.326 · 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.

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
Published2019
Admission routes1
Has abstractyes

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