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Record W6986855105

Renewing the Conversation: Monetary Award Governance

2023· article· en· W6986855105 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPosition (finance)Corporate governanceHigher educationPlan (archaeology)Monetary policyInclusion (mineral)
DOInot available

Abstract

fetched live from OpenAlex

In Canada, providing access to post-secondary education to everyone who wants it, is both a noble and multifaceted notion. This Organizational Improvement Plan (OIP) addresses one facet of accessibility to Lynnwood University (LYNU; a pseudonym), with a focus on monetary awards (e.g. scholarships). Like many institutions, LYNU has made public commitments in support of equity, diversity, and inclusion (EDI), and has increased efforts to recruit equity-deserving students using monetary awards which will help offset concerns of student affordability. Access to financial resources is a key factor for many students and without it, they may be unable to pursue their education as monetary awards can provide some or all financial resources needed to pay for tuition and living expenses. LYNU monetary awards are governed under institutional policies that hold students to academic requirements, and students who do not meet these conditions will have their award funding rescinded. Students who lose their award are often placed in a position of financial distress, and some will have to abandon their studies as they can no longer afford to study at LYNU or be forced to take on employment to supplement their income which leaves less time to focus on their academic assignments. This OIP recommends immediate changes to monetary award policies at LYNU which will be considered radical by some, and long overdue by others, but will be focused on improving student access to post-secondary education and encouraging regular reviews of policies through an EDI lens.

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 categoriesScience and technology studies, Insufficient 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 score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.145
GPT teacher head0.391
Teacher spread0.246 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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