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Record W4312043088 · doi:10.29173/ijll21

Swimming with teddy bears and sharks: Changes to a tenure, promotion, and merit award system within resistant institutional structures and interests.

2022· article· en· W4312043088 on OpenAlexaff
Dan Laitsch, Michelle Pidgeon, Nathalie Sinclair, Lynn Fels

Bibliographic record

VenueInternational Journal for Leadership in Learning · 2022
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsScholarshipPublic relationsPromotion (chess)Equity (law)SociologyAutonomyHigher educationInclusion (mineral)InstitutionPolitical sciencePedagogyPsychologySocial scienceLaw

Abstract

fetched live from OpenAlex

In 2017 the Faculty of Education (FoE) at Simon Fraser University engaged in a research-based review of its Faculty Tenure and Promotion (FTP) guidelines in an effort to better understand the scope of scholarship, teaching, and service within the faculty; to provide recommendations for how the quality of scholarship, teaching, and service might best be evaluated; and to better define the evidence that faculty members might provide the Faculty Tenure and Promotion Committee (FTPC) for assessing each of these components of academic work. This paper offers an account of the changes made—which were specific to our faculty but involved elements common in other faculties and at other universities—and the various personal and institutional constraints at play throughout the process. We highlight three different scales at which we worked that relate to issues of equity and inclusion, personal autonomy and self-motivation, and the fantasy of the objectivity of numbers. Since we have come to see the institution as the resistant milieu and therefore our work as challenging institutional structures and norms, we frame our process in terms of multiple acts of refusal. We show how these acts relate to an integrated model of policy analysis and explore our continuing efforts to implement these changes to advance principles of equity, inclusion, and diversity in our faculty and in our work. While the story is told by the four authors of this paper, we are representing the important work done by a broader team of seven who engaged in this work.[1]
 
 [1] While the four authors of this paper took responsibility for telling this story as we feel we lived it, the credit for the work accomplished over the course of this journey goes to all members of the committee, who have also had a chance to review and contribute to this article (listed alphabetically): Pooja Dharamshi, Lynn Fels, Huamei Han, Dan Laitsch, Michael Ling, Michelle Pidgeon, and Nathalie Sinclair.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
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
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.112
GPT teacher head0.408
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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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