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Record W1549756619 · doi:10.22329/jtl.v7i2.2901

Por Llanos y Montañas: Creemos en la Historía: An Inquiry into the 1961 Cuban Literacy Campaign using Photographic Representation

2011· article· en· W1549756619 on OpenAlexaffvenue
Joanne C. Elvy

Bibliographic record

VenueJournal of Teaching and Learning · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsAlgoma University
Fundersnot available
KeywordsPresentation (obstetrics)MetaphorLiteracyContext (archaeology)Representation (politics)SociologyCitizenshipValue (mathematics)Government (linguistics)Gender studiesMedia studiesPedagogyHistoryPolitical sciencePoliticsLinguisticsLaw

Abstract

fetched live from OpenAlex

In 1961, the Revolutionary government in Cuba initiated a literacy campaign that became the vehicle for social change in the country, affirming the value of education, healthcare, citizenship, professional development and the concept of family and community. As an artful researcher revisiting the impact of this educational initiative, my intent was to incorporate photographs into my research as a kind of language, a felt knowledge. Photography thus became a vital part of my methodological process as an important research and presentation tool, in respect to my engagement as a researcher from outside the Cuban experience, together with the audience’s interaction with the resulting images (Cixous, Barthes, Jongeward, Robins, et al). The photograph has also been a metaphor for the complexity of how Cuba is understood within an historical context; in how it deflects from linear readings of past events, into a space where stories can be revisited as part of a shared experience (Irwin-Zarecka, Steedman, Thelen, et al).

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.059
GPT teacher head0.354
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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2011
Admission routes2
Has abstractyes

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