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Record W7027882876

The Digital Transformation of Marketer Identities
\nin Figured Worlds

2022· dissertation· en· W7027882876 on OpenAlexaboutno aff

Bibliographic record

VenueDurham e-Theses (Durham University) · 2022
Typedissertation
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsnot available
Fundersnot available
KeywordsConstruct (python library)PopularityIdentity (music)Reading (process)PragmatismDigital transformationRelation (database)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

The digital transformation of marketing has been ongoing for more than three decades but the \nbreadth and depth of change in the last five years has been unprecedented. We know from \nextensive research on identities in organisations that change in work practices can prompt \nidentity work, yet there has been relatively little prior research about marketer identities. \nMoreover, there has been even less research about marketer identities relating to digital \ntransformation. This thesis addresses these gaps; however, it does so by looking at the \nintersection of marketer identities and digital transformation via a Pragmatist reading of Holland \net al.’s (1998) concept of Figured Worlds, a social practice theory of identity with roots in \nVygotsky, Bakhtin, Mead, and Bourdieu. This approach enabled the study of processes of \ntransformation in relation to the various artefacts which make up figured worlds, such as \nvocabularies, practices, and materialities which come together to construct understandings about \n‘how things work’ or what is considered ‘normal’ by the people who inhabit them. The main \nbody of the thesis centres on an ethnographically-oriented case study of the marketing \ndepartment of a large Canadian NGO (Canango) in the process of shifting from a traditional \n‘NGO helper’ culture to a so-called ‘Agile marketing’ culture based on project management \npractices originating in software development that have been growing in popularity among \npractitioners. The thesis identifies a number of ‘classes’ of marketer identities: managerially \nsupplied ; technologically afforded ; socially afforded ; emergent ; and, performed along with what \neach type enables one to do. Using ideas from Figured Worlds theory and multimodal discourse \nanalysis, a heuristic framework is then developed made of the elements ‘ matter ’ (phenomena), \n‘ meaning ’, mediators , ‘ me ’ (identity) and ‘ motion ’ (action) to study how these identities are \nused to accomplish contextual goals. This framework is then applied to study the way that three people variously appropriated or resisted a particular supplied identity: the ‘Agile organiser’. \nFinally the ideas developed through the first three phases of the thesis are applied in a final phase \nin which Canango begins using a new digital collaborative work platform. The study looks at the \nidentity implications of this move, evidencing the ways in which the work platform serves as a \n‘bridge’ between worlds and how such bridges may be used to change worlds and make new \nones.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.025
Scholarly communication0.0170.016
Open science0.0010.010
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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 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
Published2022
Admission routes1
Has abstractyes

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