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Record W247321000 · doi:10.17161/iallt.v12i3-4.9010

Language Laboratory Administration

2019· article· en· W247321000 on OpenAlexaff
A. J. Ciceran, R. G. Dahms

Bibliographic record

VenueIALLT Journal of Language Learning Technologies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsBrock University
Fundersnot available
KeywordsAdministration (probate law)Computer sciencePolitical science

Abstract

fetched live from OpenAlex

It is the intent of this article to provide a framework of selected administrative guidelines for new or newly appointed Language Laboratory Directors and Supervisors, as well as those with considerable experience, who may be advertising new positions, upgrading their departments, or formulating future plans and projects.While the latter may find certain of these guidelines rather elementary, the authors hope that many of the others will suggest new possibilities and philosophies of administration and operation.~major aim is to instill a sense of purpose and direction in daily Language Laboratory endeavourS>The reader will soon note that the guidelines (most of which are posed as questions) do not begin with "nuts and bolts" basics such as acquisition and maintenance of equipment, space requirements, hiring procedures and so on, but concentrate rather on the attitudes, philosophies, duties and responsibilities of both the lab Director and his personnel.The bias underlying the guidelines is that the lab works best when it is properly and fully utilised as a copartner with language departments which view its facilities and personnel as an integral part of their programmes, and which design their programmes with that in mind.Consequently, the article gives the language lab Director an opportunity to appraise his own situation, to ascertain where he fits into the general framework, and to assess his own responsibilities and attitudes, as well as those of his personnel.The focus then shifts from strictly internal lab administration and operation to relations with the faculty and, finally, to externally oriented activities.

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)0.023
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.441

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0080.003
Scholarly communication0.0110.004
Open science0.0030.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1320.120

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 head0.023
GPT teacher head0.412
Teacher spread0.389 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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Same venueIALLT Journal of Language Learning TechnologiesSame topicInterpreting and Communication in HealthcareFrench-language works237,207