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Record W7010304069

From graduate school to the outside world: a graduate student organized session Designing your professional career profile for increased visibility

2021· article· en· W7010304069 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMollusks and Parasites Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)ThrivingVisibilityGraduate studentsCareer pathGraduate educationCurriculumPanel discussion
DOInot available

Abstract

fetched live from OpenAlex

From graduate school to the outside world: a graduate student organized session\nDesigning your professional career profile for increased visibility\nPanellists:\n● Prof. Bipasha Baruah (Canada Research Chair in Global Women’s Issues, Western University) and Cam Malthaner (Career Education Coordinator, Western University)\nRationale: The path to obtaining a graduate degree is laden with challenges and opportunities intended to prepare students to be significant contributors to society. How can graduate students take full advantage of the graduate school experience to prepare themselves for a thriving career in academia and beyond. As academic job windows are constricting, how can graduate students present their experiences to reflect the skills that potential employers search for? How do they strategically enhance their visibility to potential employers through various trending professional web pages such as Linkedin? What tools are available and how can students make the best of these options? These and more questions will be addressed in this insightful panel discussion. This panel will include short presentations by the panelists and students will have the opportunity to ask further questions after the presentations. Any questions you have in advance can be sent to Eunice Annan-Aggrey (eannanag@uwo.ca) and Aislinn Adams (aadams59@uwo.ca).\n*Please note this session will be recorded and posted on this page after the conference.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.033
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.236
GPT teacher head0.363
Teacher spread0.127 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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