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Record W4405460160 · doi:10.1177/15586898241303319

Examining the Integrative Potential of Visual Timelines in Mixed Methods Research

2024· article· en· W4405460160 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.

Bibliographic record

VenueJournal of Mixed Methods Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsChildren’s Health Research InstituteUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsTimelineMultimethodologyComputer scienceManagement scienceData sciencePsychologyMathematics educationEngineeringStatisticsMathematics

Abstract

fetched live from OpenAlex

Timelines are analytic collection and dissemination tools that visually integrate temporal events with data to enhance analytic depth and reveal contextual insights. Despite their integrative potential, the use of timelines in mixed methods research has not been examined. In response, we conducted a methodological review of timelines in mixed methods. The 39 included articles emphasized timelines in data collection with participant communication and contextual analytic benefits. Predominant concerns surrounded the complexity of data presentation. Emphasis on the qualitative data arm was noted and highlighted opportunities to develop timelines into a more thoroughly integrated mixed methods research tool. This review promotes best practices and wider use of timelines to advance mixed methods integration using visual methods, moving beyond the joint display.

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)0.498
metaresearch head score (Gemma)0.154
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.718
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4980.154
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.006
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 head0.801
GPT teacher head0.779
Teacher spread0.023 · 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