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Record W7132939489

The New Normal? The Practice of Doctoral Education in a Global Pandemic

2022· dissertation· W7132939489 on OpenAlexaboutno aff
Alison Elizabeth Jefferson

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsSocializationDistancingConceptual frameworkHigher educationPandemicDoctoral studiesThe Conceptual FrameworkQualitative research
DOInot available

Abstract

fetched live from OpenAlex

There has been an increasing interest in doctoral education in recent years, and an increase in the number of doctoral graduates as institutions and nations strive to be competitive in the global knowledge economy, making doctoral education a prescient issue. There is very little existing literature on doctoral education in Canada. In the broader, existing literature, a socialization framework is frequently employed to explore the student’s journey from novice to scholar. A significant factor in this socialization has been the global COVID-19 pandemic, with the Canadian response first being felt in March 2020. In some provinces, some of the COVID-19 social distancing measures remained until early 2022. To address the broad aim of this research — to attempt to understand doctoral students’ perceptions, experiences, and socialization during the COVID-19 pandemic, contextualizing these aspects using Bourdieu’s conceptual tools — the following two-part research question was addressed: Firstly, how were students’ perceptions and experiences of their doctoral programs affected in the immediate response to the COVID-19 pandemic? And secondly, how can Bourdieu’s conceptual tools help us conceptualize students’ experiences? Semi-structured interviews were conducted with 18 doctoral students across various disciplines and departments at three research-intensive universities in one Canadian province. A fundamental aspect of this thesis was the application of Pierre Bourdieu’s conceptual tools of habitus, capital, and field, both in the design of interview questions and examination of the participant responses, to explore doctoral student experience both generally and with specific reference to experiences between March 2020 and the date of their interview, with the final interview occurring July 2021. The results suggested that previously described factors affecting socialization were exacerbated during this time. The expectations placed on students and the valued activities for socialization remained unchanged, but how students perceived those expectations and experienced those activities changed significantly. The research revealed that long-standing assumptions of doctoral study as leading to an academic faculty position are not only outdated but may be actively hindering socialization. This research advances that a new field of doctoral education has emerged due to pandemic adaptations, which has implications for the design of future doctoral programs.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designlow
grokno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designlow
opusno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.160
GPT teacher head0.595
Teacher spread0.435 · 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

Labeled directly by 3 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designOther design · Qualitative
Domainnot available
GenreOther · Empirical

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
Published2022
Admission routes1
Has abstractyes

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