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Record W7029314428

Investigating Supports and Barriers Affecting Black Students’ Enrolment and Experiences within Graduate Studies

2023· dissertation· en· W7029314428 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2023
Typedissertation
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Thematic analysisGraduate studentsQualitative researchConceptual frameworkHigher educationConceptual modelGraduate researchThe Conceptual Framework
DOInot available

Abstract

fetched live from OpenAlex

The goal of this research study was to identify and examine the supports and barriers affecting Black students’ enrolment and experiences within graduate studies. Using a qualitative approach, I focused on the lived experience of N = 10 current Black graduate students attending universities located in Southern Ontario. Using a deductive approach, this study utilized the theoretical and conceptual framework which locates mentorships as the main form of support, and Socio-economic Status (SES) as the main Barrier when considering the enrolment and experiences of Black students into graduate studies (LeBlanc, 2016; Walpole, 2003). Each of the participants took part in a 30–45-minute semi-structured interview, and we asked about their overall graduate studies experience, along with which support and Barrier they found during the enrolment process, and throughout the course of their degree. Results derived from thematic analysis focusing on participants' support revealed two main themes: 1) relationships with individuals, and 2) university community bonds. These themes provided further analysis, which paved the way for the development of sub-themes. Relationships with individuals provided three additional subthemes: 1) relationships with their mentor, 2) relationships with their friends and peers, and 3) relationships of kinship. While university community bonds provided its own three additional sub-themes: 1) race/ethnic based student groups 2) university athletics, and 3) diversity within the program/university. Meanwhile results focusing on participants’ barriers revealed two main themes: 1) being a First-Generation Student (FGS), and 2) financial considerations, which was further split into the sub-themes of Graduate Funding Packages (GFPs) and SES (Participant and Participant Family). Furthermore, concepts such as Advice to Younger Students, and Conceptual Duality were also discussed, in addition to limitations and future research.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.020
GPT teacher head0.244
Teacher spread0.224 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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