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Record W21335688

La organización escolar y los límites de la mediación de los inspectores en los institutos de secundaria

2006· article· en· W21335688 on OpenAlexaboutno aff
Ángel Lorente Lorente

Bibliographic record

VenueAvances en supervisión educativa · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsMediationArbitrationScope (computer science)StructuringFunction (biology)Order (exchange)Advice (programming)Reflection (computer programming)PedagogyInstitutionHumanitiesSchool administrationPsychologySociologyPolitical sciencePublic relationsBusinessComputer scienceLawPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

We are reporting on a recent experience with Health Informatics (HI) teaching at undergraduate degree level to an audience of HI and Pharmacy students. The important insight is that effective teaching of clinical informatics must involve highly interactive, applied components in addition to the traditional theoretical material. This is in agreement with general literature underlining the importance of simulations and role playing in teaching and is well supported by our student evaluation results. However, the viability and sustainability of such approaches to teaching hinges on significant course preparation efforts. These efforts consist of time-consuming investigations of informatics technologies, applications and systems followed by the implementation of workable solutions to a wide range of technical problems. In effect, this approach to course development is an involved process that relies on a special form of applied research whose technical complexity could explain the dearth of published reports on similar approaches in HI education. Despite its difficulties, we argue that this approach can be used to set a baseline for clinical informatics training at undergraduate level and that its implications for HI education in Canada are of importance.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.334
Teacher spread0.328 · 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
Published2006
Admission routes1
Has abstractyes

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