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Record W4407297953 · doi:10.61824/dma.vi25.732

Researcher trajectories, intersections, and multiple consciousness

2024· article· en· W4407297953 on OpenAlexaffabout
Adrienne S. Chan

Bibliographic record

VenueDyskursy Młodych Andragogów. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsConsciousnessPsychologyComputer scienceCognitive scienceNeuroscience

Abstract

fetched live from OpenAlex

This chapter is a reflection on the places and spaces that have shaped my research and my writing. The chapter highlights my research trajectory as a researcher and academic at a university in British Columbia, Canada. Researcher positionality is a key concept in considering my researcher journey. This chapter takes a journey that is highlighted by family history, being Chinese, a settler, and a non-Indigenous researcher working with Indigenous peoples. There are tensions as well as learning experiences that are the results of working in research. These evolve into my awareness of triple consciousness, intersectionality, co-researcher relationships, and how I move forward as a facilitator for change. As a woman of colour and researcher, I examine the multiple locations that have affected my research experiences. The lessons learned from my engagement in different research projects sheds a light on how one can go forward meaningfully, making choices, as a researcher and concurrently navigate community and academic spaces. My research context draws from a focus on diversity, social justice, anti-racism, community-engaged research, and research relationships. This has led me to becoming an activist-researcher.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.168
GPT teacher head0.513
Teacher spread0.345 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes2
Has abstractyes

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