MétaCan
Menu
Back to cohort
Record W1797234760 · doi:10.28945/3403

Generating Benefits and Negotiating Tensions through an International Doctoral Forum: A Sociological Analysis

2016· article· en· W1797234760 on OpenAlex
Guanglun Michael Mu, Jia Ning, Yongbin Hu, Hilary Hughes, Xiaobo Shi, Mu-chu Zhang, Jennifer Alford, Merilyn Carter, Jillian Fox, Jennifer Duke, Matthew Flynn, Huanhuan Xia

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

VenueInternational journal of doctoral studies · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSociologyNegotiationContext (archaeology)Power (physics)BeijingPublic relationsField (mathematics)Social capitalChinaPedagogySocial sciencePolitical science

Abstract

fetched live from OpenAlex

Workshops and seminars are widely-used forms of doctoral training. However, research with a particular focus on these forms of doctoral training is sporadic in the literature. There is little, if any, such research concerning the international context and participants’ own voices. Mindful of these lacunae in the literature, we write the current paper as a group of participants in one of a series of doctoral forums co-organised annually by Beijing Normal University, China and Queensland University of Technology, Australia. The paper voices our own experiences of participation in the doctoral forum. Data were drawn from reflections, journals, and group discussions of all 12 student and academic participants. These qualitative data were organised and analysed through Bourdieu’s notions of capital and field. Findings indicate that the doctoral forum created enabling and challenging social fields where participants accrued and exchanged various forms of capital and negotiated transient and complex power relations. In this respect, the sociological framework used provides a distinctive theoretical tool to conceptualise and analyse the benefits and tensions of participation in the doctoral forum. Knowledge built and lessons learned through our paper will provide implications and recommendations for future planning of, and participation in, the doctoral forum series and similar activities elsewhere.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.453
GPT teacher head0.571
Teacher spread0.117 · 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