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Record W180999183

Completing a Graduate Degree: A Case of a Female Student.

2011· article· en· W180999183 on OpenAlexaboutno aff
Kapil Dev Regmi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipSupervisorGraduate studentsMedical educationPedagogyPsychologyGraduate educationSociologyManagementPolitical scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper was written as an assignment for one of my courses while pursuing a graduate degree in the Department of Education Studies at the University of British Columbia (UBC), Canada. I have made an attempt to explore perceptions and experiences of a female graduate student on four different aspects of her family and academic life. The four aspects that emerged as the themes while analysing interview transcript are: personal and family life; gender differences; funding and scholarship; and the role of supervisor. The paper also present how the interview was conducted, how the data were generated and how analysis was done. At the end of the paper I have presented my reflections. This short and single-participant semi-structured interview research concludes with three basic findings as major impeding factors for a successful completion of a graduate programme, especially by a female student. The three findings are: female graduate students still face many challenges- as systemic barriers- that are more severe than their male counterparts face; financial problem is still a strong impeding factor that associate with all other major and minor barriers for the completion of a graduate degree; and finally, the relationship between a graduate student and her/his supervisor and the latter’s expertise in the area of student’s research interest is one of the significant factors for the successful completion of a graduate programme.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.365
GPT teacher head0.406
Teacher spread0.041 · 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 designObservational
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
Published2011
Admission routes1
Has abstractyes

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