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Record W4320920473 · doi:10.1080/15575330.2023.2178473

You do not know what you have until it is gone: The importance of face-to-face interactions in local economic development

2023· article· en· W4320920473 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCommunity Development · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsWestern University
Fundersnot available
KeywordsFace (sociological concept)Face-to-facePublic relationsBusinessTacit knowledgeSocial distanceEconomic growthCoronavirus disease 2019 (COVID-19)Political scienceSociologyKnowledge managementEconomicsComputer scienceMedicine

Abstract

fetched live from OpenAlex

To contain the 2019 coronavirus, many localities were placed on lockdown and were required to follow social distancing guidelines implemented by upper-level governments. A consequence of these containment measures was that local practitioners had to conduct economic development remotely, an activity traditionally centered around face-to-face interactions. Thus, this raises the question, how important is face-to-face contact for local economic development? To answer this question, in-depth interviews were conducted with thirty-seven senior management economic development practitioners in the Province of Ontario, Canada from 2019 to 2020. The analysis found that face-to-face contact is highly important for practitioners’ economic development efforts because it, among other things, facilitates the creation and transmission of tacit knowledge between practitioners as well as with businesses, community organizations, and other stakeholders.

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.

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)0.000
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 score0.484
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.004

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 head0.084
GPT teacher head0.298
Teacher spread0.213 · 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