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Record W2614447022 · doi:10.18260/1-2--19901

“Professional” Acts: Analyzing Sites of Identity and Interactive Response in Chemical Engineering Students

2020· article· en· W2614447022 on OpenAlexaffabout
Deborah Tihanyi, Penny Kinnear

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdentity (music)Computer scienceHuman–computer interactionAesthetics

Abstract

fetched live from OpenAlex

Professional" Acts: Analyzing sites of identity and interactive response in chemical engineering studentsIn September 2012, we began a five-year longitudinal study following eleven (11) Chemical Engineering and Applied Chemistry (CHE) students who began their second year of study in 2012-2013.The study focuses on the development of professional identity and voice in CHE students at the University of Toronto.In this paper, we will present an analysis of one participant's experience in two related sites of learning, identity and interactive response, which will allow us to showcase early "professional" acts, the responses to them, and the ways in which they evolved over the first year of the study period.It is important to note that we have only been able to look closely at a small portion of the data collected in the first year of this five-year, longitudinal study.As a result, we are not yet in a position to extrapolate, responsibly draw firm conclusions or identify trends, nor can we identify specific curricular or pedagogical implications.What we can do at this stage is highlight some of our initial findings that will inform the analysis of the rest of the data.In this paper, we focus on Téa, 1 one of eleven participants, based on the artifacts collected to date, although reference will be made to comments and work of other participants.We hope to show through this preliminary analysis how one student uses the experiences and opportunities provided both by the curriculum and this research project to develop a sense of professionalism and how to practice it as a chemical engineer as she tries on/tries out versions of her chemical engineer identity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.004
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.453
Teacher spread0.329 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2020
Admission routes2
Has abstractyes

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