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Record W6982352025

The Impact of Cost Rental Housing: Security, Affordability and Place

2024· report· en· W6982352025 on OpenAlexaff

Bibliographic record

VenueTrinity's Access to Research Output (TARA) (Trinity College Dublin) · 2024
Typereport
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsTrinity College
Fundersnot available
KeywordsLeasehold estateRentingContext (archaeology)WorryPridePerceptionQualitative researchRental housing
DOInot available

Abstract

fetched live from OpenAlex

Overall Cost Rental is extremely successful in
\ncreating secure homes and a sense of belonging and
\nownership among residents. Survey data shows that
\n80% of residents feel very secure, and 73% say they
\n‘never’ or ‘rarely’ worry about eviction. Qualitative
\ndata underlines this, with many residents describing
\ntheir housing as a ‘forever home’.
\n• Qualitative interview data reveals that perceptions
\nof Cost Rental as providing a secure home were
\nbased on three pillars. First, tenancy arrangements
\nensure long-term, secure tenancies and allow tenants
\nto furnish and make changes to their dwelling, giving
\nthem control and autonomy. Second, the high-
\nquality nature of Cost Rental dwellings, as well as
\nthe fact that they are brand new, enhanced feelings
\nof ownership, pride and general satisfaction. Third,
\nthe professionalism of the AHBs and the positive
\nnature of the landlord/tenant relationship underpins
\nperceptions of security for residents. It should be
\nnoted that many of the above points contrast with
\nresidents’ previous experiences in the private rental
\nsector.
\nThe research also identifies three sets of
\nchallenges in relation to issues of security and
\n‘home’. First, for some research participants
\ntenancy arrangements were somewhat unclear,
\nand this impacts perceptions of security. Second,
\nfor some participants fears around loss of income
\nundermined perceptions of security, a finding
\nwhich should be seen in the context of the data
\non affordability referred to below and in Chapter
\n4. Third, despite the fact that residents view Cost
\nRental as providing a secure long-term home, a
\nmajority of research participants still expressed
\na preference for homeownership. The main
\nmotivations expressed for this include having a
\n‘house and garden’ and not paying rent in later
\nlife. This raises the question of the extent to
\nwhich Cost Rental is being perceived as a genuine
\nalternative to homeownership.The Impact of Cost Rental Housing
\nDrawing on administrative data provided by the
\nAHB project partners (see Chapter 4), the research
\nfound that on average rent represents 34.5% of
\nhousehold net income for Cost Rental residents. To
\nfurther assess affordability, the research applied
\none of the most widely used measures, which
\nexamines the proportion of households who spend
\n30% or more of their disposable income on housing
\ncosts. Only 25.2% of households pay rent that is
\nless than, or equal to, 30% of their net income.
\nThe research also employed the more robust
\n30/40 measure of affordability, which allows us
\nto identify the proportion of households who fall
\nwithin the bottom 40% of the income distribution
\nand are paying more than 30% of their net
\nincome on rent. Using this measure, just 33.1% of
\nhouseholds pay more than 30% of their net income
\non rent and are in the bottom 40% of the income
\ndistribution.
\nThere are therefore a significant number of
\nresidents who do not meet some of the most
\nwidely used benchmarks for affordable housing.
\nThis potentially poses a risk for both landlords
\nand residents, and hence to the sector as a whole.
\nAffordability is complex and it appears that more
\nconsideration needs to be given to clarify what
\nconstitutes success in terms of Cost Rental’s
\nobjectives with regard to affordability.
\nThe research also finds that half of respondents
\nare currently paying more rent in Cost Rental
\nthan in their previous housing. Excluding outliers,
\ncost rents are on average 1.10 times the rent
\npaid by tenants in their previous private rental
\naccommodation, i.e. slightly higher. It should be
\nnoted that for some research participants their
\nCost Rental home was significantly larger than
\ntheir previous accommodation, and therefore this
\nis not a like-for-like comparison. Interviews show
\nthat when considering the affordability of their
\ncost rents, participants take into account that
\nCost Rental offers a lot more than their previous
\naccommodation, both in terms of the quality of the
\ndwelling and security of tenure.
\nThe survey found that 83% of respondents
\ndescribe their rent as ‘very’ or ‘fairly’ affordable.
\nQualitative data supports this, with participants
\ntypically describing rent as ‘fair’ and ‘not a burden’.
\nMoreover, during interviews participants often
\ncompared cost rents to rents for private rental
\nproperties currently on the market, which are
\ntypically significantly higher than cost rents. At the
\ntime of data collection, no research participants
\nwere in receipt of HAP and research participants
\nwere not aware of the role of HAP or other rent
\nsubsidies in Cost Rental housing.
\nCost Rental appears to be supporting the
\ndevelopment of vibrant and diverse communities.
\nAlmost 80% of survey respondents were ‘very’ or
\n‘somewhat’ positive about their neighbourhood,
\nwith 70% feeling ‘very’ or ‘somewhat’ part of a
\ncommunity. The research found no evidence of
\nstigma associated with Cost Rental.
\nThe research found that location did not emerge
\nas a major factor in tenants’ decision to apply for
\nCost Rental. Indeed, survey data shows that average
\ncommuting lengths increased somewhat, when
\ncompared to previous accommodation. Moreover,
\nsome residents identified a lack of services and
\ninfrastructure, and the issue of car dependency.
\nDuring interviews, residents described a nuanced
\npicture of their decision to apply for Cost Rental
\nhousing and their experiences in it, which involved
\nweighing up affordability, dwelling size and
\nstandard, location and lifestyle factors

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)0.009
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0020.004
Research integrity0.0000.003
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 head0.248
GPT teacher head0.463
Teacher spread0.216 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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