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Record W2184255934

PERCEPTIONS OF GRADUATE SUPERVISION: RELATIONSHIPS WITH TIME OF REFLECTION AND POST-SECONDARY CLIMATE

2013· article· en· W2184255934 on OpenAlexvenueaboutno aff
Elizabeth Graham, Shannon Gadbois

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2013
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPsychologyPerceptionAuditAccountabilityMedical educationOrganizational cultureGraduate studentsPedagogyPublic relationsManagementPolitical scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses the similarities and differences between Canadian doctoral students and new faculty members regarding their experiences with and perceptions of their graduate supervisors and mentoring. Participants’ responses were considered in light of the current post-secondary culture that emphasizes increased productivity and accountability of faculty members and the student as customer (e.g., Turk, 2000). An examination of survey and interview responses from participants showed that whereas both groups valued supervision that includes both career and psychosocial functions of mentoring (Kram, 1983), doctoral students tended to place more emphasis on the psychosocial functions than did the new faculty. In addition, although, in general, both groups gave more favourable ratings of their supervisors for career as opposed to psychosocial functions, new faculty members were more satisfied with their supervisors and rated their supervisors higher on most mentoring functions. These differences between groups were considered in light of universities’ adoption of a managerial, audit culture (e.g., Cribb & Gewirtz, 2006) that encourages students to perceive themselves as consumers and requires faculty to meet competing demands on their skills and time.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.342
Teacher spread0.295 · 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.

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

Citations1
Published2013
Admission routes2
Has abstractyes

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