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Record W2894782313

Enhancing Faculty Involvement in Program Review

2018· article· en· W2894782313 on OpenAlexaboutno aff
Georgette Crawford

Bibliographic record

VenueScholarship@Western (Western University) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessComputer scienceEngineering ethicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

This Organizational Improvement Plan provides a pathway to addressing the organizational problem of enhancing faculty involvement in program review, such that programs of instruction undergo a meaningful and rigorous review process that results in program improvement. This problem of practice is set in the context of a large, urban Ontario public college. The relevancy of this problem is born out of an increasing climate of accountability and the performative nature of the provincial quality assurance system’s audit process. A contextual and historical analysis illustrates how adverse faculty-management relations and neoliberalism have affected faculty autonomy, leading to the marginalization of faculty in quality assurance processes. An organizational analysis reveals the incongruence between a growing audit culture, embedded in the formal organizational structure, and faculty culture, disallowing the meaningful participation of faculty in the determination of program quality. The proposed solution employs distributed leadership practice to engage faculty planning and design of program review in order to instill in this critical group more meaning and ownership of the process. Coupled with this is an authentic leadership approach that builds a trusting and collaborative relationship between faculty and management. Proposed theories for leading, monitoring, and communicating change are outlined.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.349
GPT teacher head0.488
Teacher spread0.139 · 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
Published2018
Admission routes1
Has abstractyes

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