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Record W2220848092 · doi:10.21810/sfuer.v1i.331

Faux Connaître: Getting It and Not Getting It

2007· article· en· W2220848092 on OpenAlexaffvenue
Hartley Banack, Catherine Broom, Heesoon Bai

Bibliographic record

VenueSFU Educational Review · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPower (physics)NegationSociologyEpistemologyInstitutionTerminologyDreamPolitical sciencePublic relationsPsychologySocial sciencePhilosophy

Abstract

fetched live from OpenAlex

Borders not only limit contact and exchange but they often connect and create ways of communication and interaction. To establish and maintain both limits and contact, power must come into play. Thus borders act as a “technology of power,” to use Foucault’s terminology. While the Foucauldian decentralization of power from institutionalized centres does not directly comment on ethics of power, it helps us to understand better the complexity of ethical relationships that emerge from the workings of power through a myriad of borders. This panel will consider Foucauldian perspectives on how power might operate within a proposal of education with/out borders, especially as it might pertain to our Faculty of Education at Simon Fraser University. Panellists will be asked to discuss the following questions: 1) Might Foucault’s works ever suggest a possibility of living without borders and limits? What is the implication of this question for an educational institution like ours? 2) What could a notion of ‘without’ imply in terms of a utopian dream and an epistemological negation that posits and positions power relations?

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.012
Scholarly communication0.0050.008
Open science0.0010.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.086
GPT teacher head0.455
Teacher spread0.369 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2007
Admission routes2
Has abstractyes

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