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Record W4387860459 · doi:10.1002/pra2.910

Navigating Higher Education: Insights from <scp>First‐Generation</scp> Doctoral Students

2023· article· en· W4387860459 on OpenAlexaffabout
Cansu Ekmekcioglu

Bibliographic record

VenueProceedings of the Association for Information Science and Technology · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntermediaryThematic analysisHigher educationSpace (punctuation)Key (lock)PopulationFace (sociological concept)Public relationsSociologyKnowledge managementPedagogyPolitical scienceQualitative researchComputer scienceBusinessMarketingSocial science

Abstract

fetched live from OpenAlex

ABSTRACT Access to higher education is a form of capital that is not always equally distributed. First‐generation doctoral students (FGDSs) face unique challenges and barriers which can make it difficult for them to navigate academic and institutional structures and access key resources and support. We present preliminary findings from interviews with 8 FGDS participants who pursue doctoral degrees in the field of information science in Canada. Interviews focused on identifying FGDSs' information practices in their pursuit of higher education. An inductive thematic analysis revealed the diverse information needs and sources utilized by this understudied population. The results provide insights about affective dimensions of information seeking and the role of mentors as key information intermediaries in supporting more diverse, inclusive, and equitable space for FGDSs. The poster concludes with implications for practice to improve the interfaces between FGDSs and higher education institutions as well as the broader academic landscape.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.036
GPT teacher head0.344
Teacher spread0.308 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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