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Record W4384694311 · doi:10.22215/etd/2023-15564

Not All Who Want To, Can--Not All Who Can, Will: Extending Notions of Unconventional Doctoral Dissertations

2023· dissertation· en· W4384694311 on OpenAlexaffabout
Brittany Amell

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsCarleton University
FundersSchool of Linguistics and Applied Language Studies
KeywordsScholarshipCuriosityNarrativePrivilege (computing)IndigenousSociologySkepticismEthnographyEpistemologyPolitical sciencePsychologyLawLiteratureSocial psychologyPhilosophyArt

Abstract

fetched live from OpenAlex

My research destabilizes imaginings of dissertations--conventional and otherwise--by highlighting a range of doctoral dissertations that, seemingly against all odds, manage to diverge from well-worn epistemic and textual paths. Whether it's a dissertation from South Africa whose author brings auto-ethnography and illness narratives into a discipline known for its skepticism of anything qualitative (Richards, 2012), a dissertation from Canada whose author purposely eschews standard edited academic English in order to privilege traditional Indigenous knowledges (Stewart, 2015), or a dissertation from the United States whose author coded and designed a digital scholarly edition of Ulysses without writing a single chapter in the process (Visconti, 2015), my research questions what brings these dissertations together while also considering what sets them apart. To reach a contextualised understanding of unconventional dissertations, including how they are produced and received, I adopt a textographic approach to the study of writing. Informed by this approach, as well as my stance towards writing overall, this dissertation draws on data that includes questionnaire responses, transcripts from unstructured interviews with writers of unconventional dissertations, and unconventional dissertations. Findings indicate that tendencies to conflate 'doctoral dissertations' with conceptions of legacy forms of scholarly communication still prevail. At the same time, the present study demonstrates how some dissertations may appear conventional on the surface to belie the unconventionality lurking below. Even entrenched forms of scholarship can shift when the functions and values motivating these forms are approached with open curiosity. Finally, while this study confirms widespread views that not all who want to create an unconventional dissertation will be able to, it also highlights some reasons for why those who can create unconventional dissertations may still choose to refrain. Framed as a response to urgent calls for critical examinations of how scholarly knowledge is produced, communicated, and assessed, this study contributes to a small but rapidly growing area of research that tracks 'unconventional' or 'non-traditional' scholarly projects and their lifecycles. Finally, this study also responds to collective needs for publicly accessible resources that can be used to advocate for diverse forms of scholarship and the equitable practices and infrastructures required to sustain them.

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), 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 score0.726
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.061
GPT teacher head0.342
Teacher spread0.281 · 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 routes2
Has abstractyes

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