MétaCan
Menu
Back to cohort
Record W3135378787 · doi:10.1515/ijnes-2020-0057

Writing a compelling integrated discussion: a guide for integrated discussions in article-based theses and dissertations

2021· article· en· W3135378787 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsWestern UniversityOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsComputer scienceEngineering ethicsInterpretation (philosophy)Library scienceEngineering

Abstract

fetched live from OpenAlex

Article-based theses and dissertations are increasingly being used in nursing and the health sciences as an alternate format to the traditional five-chapter monograph. A unique chapter in the article-based thesis is the integrated discussion, which differs in breadth and depth as compared to the discussion for a traditional thesis monograph or journal article. For many students and faculty, the integrated discussion is a challenging chapter to write, with minimal or no published guidance available. In this article, we offer a four-step approach with templates for planning and writing an integrated discussion. We also share several lessons learned with examples from published theses and dissertations. Writing an integrated discussion can be facilitated and written more efficiently by developing a clear and detailed outline of the chapter and broad discussion points prior to drafting the text, to achieve a higher-level synthesis, analysis, and interpretation of the overall significance of the thesis findings.

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.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.079
GPT teacher head0.390
Teacher spread0.311 · 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