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The Dialogic Production of Informant Specific Maps

2017· book-chapter· en· W2766583561 on OpenAlexaboutno aff
Debra Talbot

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsDialogicTransformative learningContext (archaeology)HegemonySociologyRelation (database)PedagogyAccreditationEpistemologyPolitical scienceGeography

Abstract

fetched live from OpenAlex

Abstract The influence of extralocally produced texts, such as professional standards and systems of accreditation, on the ruling relations that govern teachers’ work and their learning about that work is a matter of concern in Australia, as it is in Canada, UK, and USA. This chapter explains how a dialogic analysis and the construction of individual maps of social relations were employed to reveal the influences that governed teachers’ learning about their work at the frontline. A dialogic analysis of research conversations about learning, based on the work of Mikhail Bakhtin, revealed the existence of both centralizing, hegemonic discourses associated with a managerial agenda and contextualized, heterogeneous discourses supportive of transformative learning. It also revealed the uneven influence of extralocally produced governing texts on both the locally produced texts and the “doings” of individuals. The production and use of “individual” maps represents a variation on the way “mapping” has generally been used by institutional ethnographers. From these informant specific maps, we can begin to observe some broad patterns in relation to the coordination of people’s “doings” both within a given context and from one context to another.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.755
Threshold uncertainty score0.743

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.300
Teacher spread0.263 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations5
Published2017
Admission routes1
Has abstractyes

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